2024

• Self-Supervised Learning of Color Constancy
  MR Ernst, FM López, A Aubret, RW Fleming, J Triesch
  International Conference on Development and Learning 2024 (ICDL)

• Learning Object Semantic Similarity with Self-Supervision
  A Aubret, T Schaumlöffel, G Roig, J Triesch
  International Conference on Development and Learning 2024 (ICDL)

• Self-Calibrating Saccade-Vergence Interactions
  FM López, M Raabe, BE Shi, J Triesch
  International Conference on Development and Learning 2024 (ICDL)

• Hippocampus and striatum show distinct contributions to longitudinal changes in value-based learning in middle childhood
  J Falck, L Zhang, L Raffington, JJ Mohn, J Triesch, C Heim, YL Shing
  eLife

• Accelerating Spiking Neural Network Simulations with PymoNNto and PymoNNtorch
  M Vieth, A Rahimi, AG Mohammadi, J Triesch, M Ganjtabesh
  Frontiers in Neuroinformatics

• Histomolecular classification of urothelial carcinoma of the urinary bladder
  AK Stoll, FJ Koll, M Eckstein, H Reis, N Flinner, PJ Wild, J Triesch
  Die Pathologie
  

• A developmental increase of inhibition promotes the emergence of hippocampal ripples
  I Pochinok, TM Stöber, J Triesch, M Chini, IL Hanganu-Opatz
  Nature Communications
  

2023

• Models of vision need some action
  C Rothkopf, F Bremmer, K Fiehler, K Dobs, J Triesch
  Behavioral and Brain Sciences
  

• Utilizing 2D-region-based CNNs for automatic dendritic spine detection in 3D live cell imaging
  FW Vogel, S Alipek, JB Eppler, P Osuna-Vargas, J Triesch, Dane Bissen, A Acker-Palmer, S Rumpel, M Kaschube
  Nature Scientific Reports
  

• CIPER: Combining Invariant and Equivariant Representations Using Contrastive and Predictive Learning
  X Xu, J Triesch
  32nd International Conference on Artificial Neural Networks (ICANN 2023)
  

• CRE: Circle relationship embedding of patches in vision transformer
  Z Yu, J Triesch
  31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023)
  

• Advancing Brain Tumor Detection with Multiple Instance Learning on Magnetic Resonance Spectroscopy Data
  D Lu, G Kurz, N Polomac, I Gacheva, E Hattingen, J Triesch
  32nd International Conference on Artificial Neural Networks (ICANN 2023)
  

• Eye-Hand Coordination Develops from Active Multimodal Compression
  FM López, BE Shi, J Triesch
  International Conference on Development and Learning 2023 (ICDL)

• Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play
  T Schaumlöffel, A Aubret, G Roig*, J Triesch*
  International Conference on Development and Learning 2023 (ICDL)
  *Equal contribution / joint last authorship

• Saccade Amplitude Statistics are Explained by Cortical Magnification
  MC Raabe, FM López, Z Yu, S Caplan, C Yu, BE Shi, J Triesch
  International Conference on Development and Learning 2023 (ICDL)

• Variability in Infant Social Responsiveness: Age and Situational Differences in Attention-Following
  Y Tang, J Triesch, GO Deák
  Developmental Cognitive Neuroscience

• Biological complexity facilitates tuning of the neuronal parameter space
  M Schneider, AD Bird, A Gidon, J Triesch, P Jedlicka, H Cuntz
  PLOS Computational Biology

• REAL-X — Robot open-Ended Autonomous Learning Architecture: Building Truly End-to-End Sensorimotor Autonomous Learning Systems
  E Cartoni, D Montella, J Triesch, G Baldassarre
  IEEE Transactions on Cognitive and Developmental Systems
  

• Synaptic logistics: Competing over shared resources
  A Hafner, J Triesch
  Molecular and Cellular Neuroscience
  

• Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair
  TM Stöber, D Batulin, J Triesch, R Narayanan, P Jedlicka
  Communications Biology
  

• Time to augment self-supervised visual representation learning
  A Aubret*, MR Ernst*, C Teuliere, J Triesch
  Eleventh International Conference on Learning Representations (ICLR 2023)
  *Equal contribution / joint first authorship

2022

• Diagnosing Epileptogenesis with Deep Anomaly Detection
  A Farahat, D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
  Proceedings of Machine Learning Research (Machine Learning for Healthcare)

• Learning torsional eye movements through active efficient coding
  Q Zhu, C Zhang, J Triesch and BE Shi
  Neuromorphic Computing and Engineering

• How to learn with intentional mistakes: NoisyEnsembles to overcome poor tissue quality for deep learning in computational pathology
  RS Mayer, S Gretser, LE Heckmann, PK Ziegler, B Walter, H Reis, K Bankov, S Becker, J Triesch, PJ Wild, N Flinner
  Frontiers in Medicine

• A mathematical model of neuroimmune interactions in epileptogenesis for discovering treatment strategies
  D Batulin, F Lagzi, A Vezzani, P Jedlicka, J Triesch
  iScience

• Compressed information is all you need: unifying intrinsic motivations and representation learning
  A Aubret, M Lefort, C Teulière, L Matignon, S Hassas, J Triesch
  NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems

• Toddler-inspired embodied vision for learning object representations
  A Aubret, C Teulière, J Triesch
  2022 IEEE International Conference on Development and Learning (ICDL)

• MIMo: A Multi-Modal Infant Model for Studying Cognitive Development in Humans and AIs
  D Mattern, FM López, MR Ernst, A Aubret, J Triesch
  2022 IEEE International Conference on Development and Learning (ICDL)

2021

• Recurrent processing improves occluded object recognition and gives rise to perceptual hysteresis
  MR Ernst, T Burwick, J Triesch
  Journal of Vision

• Contrastive Learning Through Time
  F Schneider, X Xu, MR Ernst, Z Yu, J Triesch
  SVRHM 2021 workshop @ NeurIPS

• PymoNNto: A Flexible Modular Toolbox for Designing Brain-Inspired Neural Networks
  M Vieth, TM Stöber, J Triesch
  Frontiers in Neuroinformatics

• Self-Calibrating Vision through Active Efficient Coding on a Novel Robotic Binocular Vision Platform
  J Mahn, C Wilmot, BE Shi, J Triesch
  Human-like Behavior and Cognition in Robots Workshop at the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021)
  (best poster award)

• The Development of Active Binocular Vision under Normal and Alternate Rearing Conditions
  L Klimmasch, J Schneider, A Lelais, BE Shi, J Triesch
  eLife

• OpenEyeSim 2.0: Simulation of accommodation, depth-of-field, chromatic aberration, and contrast sensitivity in a biomechanical model of the oculomotor system
  A Lichtenstein, J Triesch
  Journal of Vision September 2021, Vol.21, 2280

• A Computational Model of the Effect of Short-Term Monocular Deprivation on Binocular Rivalry in the Context of Amblyopia
  N Seeliger, J Triesch
  30th International Conference on Artificial Neural Networks (ICANN 2021)
  (best paper award)

• Unsupervised anomaly detection for diagnosing brain disorders from EEG recordings – Results from a rodent epilepsy model
  A Farahat, D Lu, S Bauer, F Rosenov, J Triesch
  Clinical Neurophysiology, Volume 132, Issue 8

• Spike Timing-Based Unsupervised Learning of Orientation, Disparity, and Motion Representations in a Spiking Neural Network
  T Barbier , C Teuliere, J Triesch
  CVPR 2021 workshop paper

• Active head rolls enhance sonar-based auditory localization performance
  LP Wijesinghe , MJ Wohlgemuth, RHY So, J Triesch, CF Moss, BE Shi
  PLOS Computational Biology

• Biological complexity facilitates tuning of the neuronal parameter space
  M Schneider, A Gidon, J Triesch, P Jedlicka, H Cuntz
  bioRxiv preprint

• Multiple Instance-Based Tumor Detection from Magnetic Resonance Spectroscopy Data
  D Lu, G Kurz, N Polomac, I Gacheva, E Hattingen, J Triesch
  AI for Public Health Workshop at ICLR'21

• Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation
  D Lu, N Polomac, I Gacheva, E Hattingen, J Triesch
  The international Conference on Acoustics, Speech, & Signal Processing (ICASSP 2021)

• Learning Abstract Representations through Lossy Compression of Multi-Modal Signals (Video) 
  C Wilmot, J Triesch
  IEEE Transactions on Cognitive and Developmental Systems (accepted)

• EEG microstate periodicity explained by rotating phase patterns of resting-state alpha oscillations
  F von Wegner, S Bauer, F Rosenow, J Triesch, H Laufs
  Neuroimage 224

2020

• An open-ended learning architecture to face the REAL 2020 simulated robot competition
  E Cartoni, D Montella, J Triesch, G Baldassarre
  arXiv preprint (arXiv:2011:13880)

• An Event-by-Event Approach for Velocity Estimation and Object Tracking with an Active Event Camera
  Q Zhu, J Triesch, BE Shi
  IEEE Journal on Emerging and Selected Topics in Circuits and Systems

• Unsupervised Learning of Spatio-Temporal Receptive Fields from an Event-Based Vision Sensor
  T Barbier, C Teulière, J Triesch
  29th International Conference on Artificial Neural Networks (ICANN 2020)
  Lecture Notes in Computer Science, volume 12397 (pp 622-633)

• Recurrent Feedback Improves Recognition of Partially Occluded Objects
  MR Ernst, J Triesch, T Burwick
  Proceedings of the 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2020)

• Integration of Vergence, Cyclovergence, and Saccades through Active Efficient Coding
  Q Zhu, J Triesch, BE Shi
  International Conference on Development and Learning and Epigenetic Robotics (ICDL 2020)

• Towards Early Diagnosis of Epilepsy from EEG Data
  D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
  Proceedings of the 5th Machine Learning for Healthcare Conference, PMLR 126:80-96, 2020

• Staging Epileptogenesis with Deep Neural Networks
  D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
  Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health (BCB 2020) 

• REAL-2019: Robot open-Ended Autonomous Learning competition
  E Cartoni, F Manella, VG Santucci, J Triesch, E Rueckert, G Baldassarre
  Proceedings of Machine Learning Research 123:142–152, 2020 (NeurIPS 2019 Competition and Demonstration Track)

• Retinal Slip Estimation and Object Tracking with an Active Event Camera
  Q Zhu, J Triesch, BE Shi
  2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS 2020)

• A Model of Brain Folding Based on Strong Local and Weak Long-Range Connectivity Requirements
  M Groden, M Weigand, J Triesch, P Jedlicka, H Cuntz
  Cerebral Cortex, bhz249

• Active efficient coding explains the development of binocular vision and its failure in amblyopia
  S Eckmann, L Klimmasch, BE Shi, J Triesch
  Proceedings of the National Academy of Sciences (PNAS)

2019

• A Deep Residual Neural Network based Framework for Epileptogenesis Detection in A Rodent Model with Single-channel EEG Recordings
  D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
  International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI 2019)

• Recurrent Connectivity Aids Recognition of Partly Occluded Objects
  MR Ernst, J Triesch, T Burwick
  arXiv preprint (arXiv:1909.06175)

• Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders
  MR Ernst, J Triesch, T Burwick
  28th International Conference on Artificial Neural Networks (ICANN 2019)
  Lecture Notes in Computer Science, volume 11729 (pp 294-305)

• Editorial: Linking experimental and computational connectomics
  A Peyser, SP Diaz, W Klijn, A Morrison, J Triesch
  Network Neuroscience 2019 3:4, 902-904

• Evaluating the Ergonomics of a Virtual Reality Software for the Diagnosis and Treatment of Amblyopia
  J Schneider, J Tittes, M Fronius, P Feige, Y Wenner, R Hess, J Triesch
  Perception 

• A Computational Model of the Development and Treatment of Anisometropic Amblyopia
  S Eckmann, L Klimmasch, BE Shi, J Triesch
  Perception 

• Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy
  D Lu, J Triesch
  arXiv preprint (arXiv:1903.08100)

• Fading Memory, Plasticity, and Criticality in Recurrent Networks
  B Del Papa, V Priesemann, J Triesch
  The Functional Role of Critical Dynamics in Neural Systems (pp 95-115)

• Autonomous Development of Active Binocular and Motion Vision Through Active Efficient Coding
  A Lelais, J Mahn, V Narayan, C Zhang, BE Shi, J Triesch
  Frontiers in Neurorobotics

• Active Efficient Coding Explains the Development of Binocular Vision and its Failure in Amblyopia
  S Eckmann, L Klimmasch, BE Shi, J Triesch
  bioRxiv preprint

2018

• From Animals to Animats 15
  P Manoonpong, JC Larsen, X Xiong, J Hallam, J Triesch
  15th International Conference on Simulation of Adaptive Behavior, SAB 2018, Frankfurt/Main, Germany, August 14-17, 2018, Proceedings (Vol. 10994). Springer.
• Learning to Touch Objects Through Stage-Wise Deep Reinforcement Learning
  F De La Bourdonnaye, C Teuliere, J Triesch, T Chateau
  2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• Robot End Effector Tracking Using Predictive Multisensory Integration
  LP Wijesinghe, J Triesch, BE Shi
  Frontiers in Neurorobotics
• Competition for synaptic building blocks shapes synaptic plasticity
  J Triesch, AD Vo, A-S Hafner
  eLife
• EEG-triggered TMS reveals stronger brain state-dependent modulation of motor evoked potentials at weaker stimulation intensities
  N Schaworonkow, J Triesch, U Ziemann, C Zrenner
  Brain Stimulation
• Stage-wise learning of reaching using little prior knowledge
  F De La Bourdonnaye, C Teuliere, T Chateau, J Triesch
  Frontiers in Robotics and AI
• An Active Efficient Coding Model of Binocular Vision Development Under Normal and Abnormal Rearing Conditions
  L Klimmasch, J Schneider, A Lelais, BE Shi, J Triesch
  International Conference on Simulation of Adaptive Behavior (2018)
  (best paper award)
• Learning Hierarchical Integration of Foveal and Peripheral Vision for Vergence Control by Active Efficient Coding
  Z Zhao, J Triesch, BE Shi
  International Conference on Simulation of Adaptive Behavior (2018)
• Neural oligarchy: how synaptic plasticity breeds neurons with extreme influence
  FI Kleberg, J Triesch
  bioRxiv (2018)
• Simulation of electromyographic recordings following transcranial magnetic stimulation
  B Moezzi, N Schaworonkow, L Plogmacher, MR Goldsworthy, B Hordacre, M Mcdonnell, N Iannella, MC Ridding, J Triesch
  Journal of Neurophysiology (2018)
• Bridging structure and function: A model of sequence learning and prediction in primary visual cortex
  C Klos, D Miner, J Triesch
  PLOS Computational Biology (2018)
• An Active Efficient Coding Model of the Development of Amblyopia
  S Eckmann, L Klimmasch, B Shi, J Triesch
  Computational and mathemtical models in vision, MODVIS (2018)
• Ongoing brain rhythms shape I-wave properties in a computational model
  N Schaworonkow, J Triesch
  Brain Stimulation (2018)
• What Leads To Shared Attention? Maternal Cues and Infant Responses During Object Play
  G Deák, A Krasno, H Jasso, J Triesch
  Infancy (2018)

2017

• Autonomous, self-calibrating binocular vision based on learned attention and active efficient coding
  Q Zhu, J Triesch, BE Shi
  Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2017

• Learning of active binocular vision in a biomechanical model of the oculomotor system
  L Klimmasch, A Lelais, A Lichtenstein, BE Shi, J Triesch
  Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2017

• Competition for a limited supply of synaptic building blocks predicts multiplicative synaptic normalization and heterosynaptic plasticity
  J Triesch, AS Hafner
  bioRxiv (2017)
• Nonrandom network connectivity comes in pairs
  FZ Hoffmann, J Triesch
  Network Neuroscience (2017)
  Documentation & code.

• Joint Learning of Binocularly Driven Saccades and Vergence by Active Efficient Coding
  Q Zhu, J Triesch, B Shi
  Frontiers in Neurorobotics, 2017
• Personalized translational epilepsy research -- Novel approaches and future perspectives: Part II: Experimental and translational approaches
  S Bauer et al.
  Epilepsy & Behavior, 2017
• Personalized translational epilepsy research -- Novel approaches and future perspectives: Part I: Clinical and network analysis approaches
  F Rosenow et al.
  Epilepsy & Behavior, 2017
• A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity
  Q Wang, C Rothkopf, J Triesch
  PLOS Computational Biology, 2017
• Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network
  B Del Papa, V Priesemann, J Triesch
  PLOS ONE, 2017
• Structural Plasticity and the Generation of Bidirectional Connectivity
  D Miner, FZ Hoffmann, F Kleberg, J Triesch
  In: "The Rewiring Brain – A Computational Approach to Structural Plasticity in the Adult Brain"
  A van Ooyen and M Butz-Ostendorf (editors) Academic Press, San Diego, 2017

• Learning multisensory neural controllers for robot arm tracking
  L Wijesinghe, M Antonelli, J Triesch, B Shi
  International Joint Conference on Neural Networks (IJCNN), 2017
• Apprentissage par renforcement profond de la fixation binoculaire en utilisant de la détection d’anomalies (Learning of Binocular Fixations using Anomaly Detection with Deep Reinforcement Learning)
  F de La Bourdonnaye, C Teulière, J Triesch, T Chateau
  ORASIS 2017 (in press)
• Learning of Binocular Fixations using Anomaly Detection with Deep Reinforcement Learning
  F de La Bourdonnaye, C Teulière, J Triesch, T Chateau
  International Joint Conference on Neural Networks (IJCNN), 2017

2016

• An active-efficient-coding model of optokinetic nystagmus
  C Zhang, J Triesch, B Shi
  Journal of Vision, 2016
• Computational connectomics
  J Triesch, C Hilgetag
  e-Neuroforum, 2016
• The dynamic connectome
  S Rumpel, J Triesch
  e-Neuroforum, 2016
• A Multi-Scale Computational Model of the effects of TMS on Motor Cortex
  H Seo, N Schaworonkow, S Jun, J Triesch
  F1000 Research, 2016
• Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring
  D Miner, J Triesch
  PLOS Computational Biology, 2016
• Precise Synaptic Efficacy Alignment Suggests Potentiation Dominated Learning
  C Hartmann, D Miner, J Triesch
  Frontiers in Neural Circuits, 2016
• OpenEyeSim: A biomechanical model for simulation of closed-loop visual perception
  A Priamikov, M Fronius, B Shi, J Triesch
  Journal of Vision, 2016
• Self-calibrating active depth perception via motion parallax
  T Prucksakorn, S Jeong, J Triesch, H Lee, N Chong
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2016
• Global and Local Statistical Regularities Control Visual Attention to Object Sequences
  A Romberg, Y Zhang, B Newman, J Triesch, C Yu,
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2016

2015

• Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network
  C Hartmann, A Lazar, B Nessler, J Triesch
  PLoS Computational Biology, 2015
• Modeling TMS-induced I-waves in human motor cortex
  J Triesch, C Zrenner, U Ziemann
  Progress in Brain Research, 2015
• Intrinsic Motivations Drive Learning of Eye Movements: An Experiment with Human Adults
  D Caligiore, M Mustile, D Cipriani, P Redgrave, J Triesch, M De Marsico, G Baldassarre
  PLoS ONE, 2015
• Key features of neural variability emerge from self-organized sequence learning in a deterministic neural network
  C Hartmann, A Lazar, J Triesch,
  24th Annual Computational Neuroscience Meeting (CNS), 2015
• Seeing [u] aids vocal learning: babbling and imitation of vowels using a 3D vocal tract model, reinforcement learning, and reservoir computing
  M Murakami, B Kröger, P Birkholz, J Triesch
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2015
• On the utility of sparse neural representations in adaptive behaving agents
  T Chandrapala, B Shi, J Triesch
  International Joint Conference on Neural Networks (IJCNN), 2015
• Real-time activity recognition via deep learning of motion features
  K Konda, P Chandrashekhariah, R Memisevic, J Triesch
  European Symposium on Artificial Neural Networks,
  Computational Intelligence and Machine Learning (ESANN), 2015

2014

• Self-calibrating smooth pursuit through active efficient coding
  C Teulière, S Forestier, L Lonini, C Zhang, Y Zhao, B Shi, J Triesch
  Robotics and Autonomous Systems, 2014
• Top-down influences on ambiguous perception: the role of stable and transient states of the observer
  L Scocchia, M Valsecchi, J Triesch
  Frontiers in Human Neuroscience, 2014
• Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures
  D Miner, J Triesch
  Frontiers in Neuroanatomy, 2014
• Robust development of synfire chains from multiple plasticity mechanisms
  P Zheng, J Triesch
  Frontiers in Computational Neuroscience, 2014
• Spike avalanches in vivo suggest a driven, slightly subcritical brain state
  V Priesemann, M Wibral, M Valderrama, R Pröpper, M Le Van Quyen, T Geisel, J Triesch, D Nikolić, M Munk
  Frontiers in Systems Neuroscience, 2014
• Differential effects of visual attention and working memory on binocular rivalry
  L Scocchia, M Valsecchi, K Gegenfurtner, J Triesch
  Journal of vision, 2014
• Emergence of task-dependent representations in working memory circuits
  C Savin, J Triesch
  Frontiers in Computational Neuroscience, 2014
• A model of TMS-induced I-waves in Motor Cortex
  C Rusu, M Murakami, U Ziemann, J Triesch
  Brain Stimulation, 2014
• A unifying theory of synaptic long-term plasticity based on a sparse distribution of synaptic strength
  D Krieg, J Triesch
  Frontiers in Synaptic Neuroscience, 2014
• Nonlinear Dynamics Analysis of a Self-Organizing Recurrent Neural Network: Chaos Waning
  J Eser, P Zheng, J Triesch
  PLoS One, 2014
• Watch the hands: infants can learn to follow gaze by seeing adults manipulate objects
  G Deák, A Krasno, J Triesch, J Lewis, L Sepeta
  Developmental Science, 2014
• Autonomous Learning of Smooth Pursuit and Vergence through Active Efficient Coding
  V Narayan, C Teulière, C Zhang, B Shi, J Triesch
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2014
• OpenEyeSim -- a platform for biomechanical modeling of oculomotor control
  A Priamikov, J Triesch
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2014
• Hide and Seek: an active binocular tracking system
  P Chandrashekhariah, J Triesch
  9th International Conference on Computer Vision Theory and Applications (VISAPP), 2014

2013

• Robust active binocular vision through intrinsically motivated learning
  L. Lonini, S. Forestier, C. Teulière, Y. Zhao, B. Shi, J. Triesch
  Frontiers in Neurorobotics, 2013
• Imitation Learning Based on an Intrinsic Motivation Mechanism for Efficient Coding
  J. Triesch
  Frontiers in Psychology, 2013
• Power spectra of the natural input to the visual system
  D. Pamplona, J. Triesch, C. Rothkopf
  Vision Research, 2013
• Visual Working Memory Contents Bias Ambiguous Structure from Motion Perception
  L. Scocchia, M. Valsecchi, K. Gegenfurtner, J. Triesch PLoS ONE, 2013
• Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
  P. Zheng, C. Dimitrakakis, J. Triesch
  PLoS Computational Biology 9(1), 2013
• Normative Models of Cortical Function
  J. Triesch
  In: "Encyclopedia of Computational Neuroscience", D. Jaeger & R. Jung (editors), 2013, Springer New York
• Learning to Share: The Emergence of Joint Attention in Human Infancy
  G. Deák, J. Triesch, A. Krasno, K. de Barbaro, M. Robledo
  In: "Cognition and Brain Development: Converging Evidence from Converging Methodologies", B. Kar (editor), 2013, American Psychological Association, Washington, DC.
• Eye's imaging process explains ganglion cells anisotropies  (2013)
  D. Pamplona, J. Triesch, C. Rothkopf
  Computational and Systems Neuroscience (Cosyne 2013)
• Autonomous learning of active multi-scale binocular vision
  L. Lonini, Y. Zhao, P. Chandrashekhariah, B. Shi, J. Triesch
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2013 Let it Learn: A Curious Vision System for Autonomous Object Learning
  P. Chandrashekhariah, G. Spina, J. Triesch
  8th International Conference on Computer Vision Theory and Applications (VISAPP), 2013

2012

• The statistics of looking: Deriving properties of retinal ganglion cells across the visual field
  D. Pamplona, J. Triesch, C. Rothkopf
  Journal of Vision, 2012
• A Unified Account of Gaze Following
  H. Jasso, J. Triesch, G. Deák, J. Lewis
  IEEE Transactions on Autonomous Mental Development, 2012
• What’s “up”? Working memory contents can bias orientation processing
  L. Scocchia, G. Cicchini, J. Triesch
  Vision Research, 2012
• Infants in Control: Rapid Anticipation of Action Outcomes in a Gaze-Contingent Paradigm
  Wang Q, Bolhuis J, Rothkopf CA, Kolling T, Knopf M, et al. (2012)
  PLoS ONE 7(2): e30884.
• The statistics of looking: Deriving properties of retinal ganglion cells across the visual field (2012)
  D. Pamplona, J. Triesch, C. Rothkopf
  12th Annual meeting of the Vision Sciences Society
• Autonomous Learning Of Robust Visual Object Detection And Identification On A Humanoid
  J. Leitner, P. Chandrashekhariah, S. Harding, M. Frank, G. Spina, A. Förster, J. Triesch, J. Schmidhuber
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2012
• A Unified Model of the Joint Development of Disparity Selectivity and Vergence Control
  Y. Zhao, C. Rothkopf, J. Triesch, B. Shi
  IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2012

2011

• Bayesian cue integration as a developmental outcome of reward mediated learning
  TH Weisswange, CA Rothkopf, T Rodemann, J Triesch
  PLoS ONE (2011) 6(7): e21575
• Predicting Ganglion Cells Variability
  D. Pamplona, J. Triesch, C. Rothkopf
  Computational and Systems Neuroscience (Cosyne 2011)
• Edge and image statistics across the visual field
  D. Pamplona, J. Triesch, C. Rothkopf
  Bernstein Conference 2011
• Familiarity-to-novelty shift driven by learning: A conceptual and computational model 
  Q. Wang, P. Chandrashekhariah, G. Spina
  IEEE 10th International Conference on Development and Learning (ICDL), 2011
• Scalable reinforcement learning through hierarchical decompositions for weakly-coupled problems
  H. Toutounji, C. A. Rothkopf, J. Triesch  
  IEEE 10th International Conference on Development and Learning (ICDL), 2011
• Reward-based learning of optimal cue integration in audio and visual depth estimation
  C. Karaoguz, T. H. Weisswange, T. Rodemann, B. Wrede, C. A. Rothkopf
  15th International Conference on Advanced Robotics (ICAR) 2011
• Emerging Bayesian Priors in a Self-Organizing Recurrent Network
  A Lazar, G Pipa, J Triesch
  Proc of the International Conference on Artificial Neural Networks (ICANN 2011)

2010

• A unified computational model of the development of object unity, object permanence, and occluded object trajectory perception
  A Franz, J Triesch
  Infant Behavior and Development, 2010.
• Independent Component Analysis in Spiking Neurons
  C. Savin, P. Joshi, J. Triesch. 
  PLoS Computational Biology, 2010.
• A Dialog on the Role of Computational Modeling in Developmental Science
  V.R. Simmering, J. Triesch, G.O. Deak, J.P. Spencer. 
  Child Development Perspectives, 2010.
• Credit assignment in multiple goal embodied visuomotor behavior
  C. A. Rothkopf, D. H. Ballard
  Frontiers in Psychology, Special Topic: 'Embodied and grounded cognition', 2010
• Vision in the natural world
  M. M. Hayhoe, C. A. Rothkopf
  Wiley Interdisciplinary Reviews: Cognitive Science, Wiley, 2010
• Structural plasticity improves stimulus encoding in a working memory model
  Savin, C. & Triesch, J
  Conference Abstract: Computational and Systems Neuroscience 2010. 
• Coordination in Sensory Integration
  Triesch, J., Rothkopf, CA. & Weisswange, TH
  In: Dynamic Coordination in the Brain: From neurons to Mind.
  Edited by C. von der Malsburg, W.A. Phillips & W. Singer.
  Strüngmann Forum Report, Vol. 5, Cambridge, MA: MIT Press.
• Computational modeling of multisensory object perception. 
  Rothkopf, CA., Weisswange, TH. & Triesch, J
  In: "Multisensory Object Perception in the Primate Brain", Naumer, MJ. & Kaiser, J. (editors). Springer, New York. ISBN: 978-1-4419-5614-9 

2009

• Image statistics at the point of gaze during human navigation
  C. A. Rothkopf, D. H. Ballard
  Visual Neuroscience, special issue on 'Natural Systems Analysis', 2009
• SORN: a Self-organizing Recurrent Neural Network
  A. Lazar, G. Pipa, and J. Triesch
  Frontiers in Computational Neuroscience, 2009.
  (Supplemental material may be found here.)
• Goal-directed learning of features and forward models
  S. Saeb, C. Weber, and J. Triesch
  Neural Networks, 2009.
• Epileptogenesis due to glia-mediated synaptic scaling
  C Savin, J Triesch, M Meyer-Hermann
  J R Soc Interface 6(37):655-668, 2009.
• Implementations and Implications of Foveated Vision
  C. Weber and J. Triesch. 
  Recent Patents on Computer Science 2(1):75-85, 2009.
• Developing a working memory with reward-modulated STDP,
  Savin, C. & Triesch, J.
  In: Frontiers in Computational Neuroscience.
  Conference Abstract: Computational and systems neuroscience. 
• Foveation with optimized receptive fields
  D. Pamplona, C. Weber, J. Triesch
  Bernstein Conference 2009
• Foveated Vision with FPGA Camera  (2009)
  G. Tushev, M. Liu, D. Pamplona, J. Bornschein, C. Weber, J. Triesch
  Bernstein Conference 2009
• A recurrent network acquires working memory properties by reward-dependent STDP
  Savin, C. & Triesch
  J. MSRL, June 2009
• Learning independent causes in natural images explains the spacevariant oblique effect
  Rothkopf, CA., Weisswange, TH. & Triesch, J
  In: Proc. ICDL 2009.
• A Neural Model for the Adaptive Control of Saccadic Eye Movements
  S. Saeb, C. Weber and J. Triesch
  Int. Joint Conf. on Neural Networks (IJCNN2009).
• Goal-Directed Feature Learning
  C. Weber and J. Triesch
  Int. Joint Conf. on Neural Networks (IJCNN2009).
• A robust biologically plausible implementation of ICA-like learning
  F. Gerhard, C. Savin, and J. Triesch
  European Symposium on Artificial Neural Networks (ESANN2009).
• Can reinforcement learning explain the development of causal inference in multisensory integration?
  Weisswange, TH., Rothkopf, CA., Rodemann, T. & Triesch, J.
  In: Proc. ICDL 2009.

2008

• Object perception is selectively slowed by a visually similar working memory load
  A. Robinson, A. Manzi, and J. Triesch. 
  Journal of Vision, 8(16):1-13, 2008. Talk video.
• Task-specific modulation of memory for object features in natural scenes
  A. Robinson and J. Triesch. 
  Advances in Cognitive Psychology, 4:1-14, 2008.
• A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity
  C. Weber, and J. Triesch
  Neural Computation 20:1261-1284, 2008.
• ICA with spiking neurons
  Savin, C. & Triesch, J.
  In: Proc. Lemanic Neurosciences Annual Meeting, Switzerland, 2008.
• Reinforcement Learning Embedded in Brains and Robots 
  C. Weber, M. Elshaw, S. Wermter, J. Triesch and C. Willmot
  In: Reinforcement Learning, I-Tech Education and Publishing, 2008. 
• A robotic model of the development of gaze following
  Kim H., Jasso H., Deak G., & Triesch, J.
  In: Proc. ICDL 2008.
• Modeling the development of causality and occlusion perception in infants
  Franz, A., & Triesch, J.
  In: Proc. ICDL, 2008.
• Predictive Coding in Cortical Microcircuits
  Lazar, A., Pipa, G., Triesch, J. 
  In: ICANN 2008.
• From Exploration to Planning
  C. Weber and J. Triesch
  Proc. Int. Conf. on Neural Networks (ICANN08).
• Understanding robustness in Random Boolean Networks
  Willadsen, K., Triesch, J. & Wiles, J.
  Alife XI, 2008.

2007

• Fading Memory and Time Series Prediction in Recurrent Networks with Different Forms of Plasticity
  Lazar, A., Pipa, G. & Triesch, J.
  In: Neural Networks 20: 312-322, 2007.
• Time Series Prediction, Fading Memory, and Error Correction in Recurrent Networks Shaped by Plasticity
  A. Lazar, G. Pipa, and J. Triesch.
  Neural Networks 20:312-322, 2007.
• Learning Sensory Representations with Intrinsic Plasticity
  N. Butko and J. Triesch.
  Neurocomputing 70:1130-1138, 2007.
• Emergence of Mirror Neurons in a Model of Gaze Following
  J. Triesch, H. Jasso, and G. Deak.
  Adaptive Behavior 15(2):149-165, 2007.
• Synergies between Intrinsic and Synaptic Plasticity Mechanisms
  J. Triesch.
  Neural Computation 19:885-909, 2007.
• To Each His Own: The Caregiver's Role in a Computational Model of Gaze Following
  C. Teuscher and J. Triesch.
  Neurocomputing 70:2166-2180, 2007.
• A reinforcement learning model of social referencing
  Jasso, H., Triesch, J. & Deak, G
  abstract presented at the Computational Cognitive Neuroscience Conference, 2007
• A computational model of glia mediated seizure induction
  Savin, C., Triesch, J. & Meyer-Hermann, M.
  In: Workshop on Seizure Prediction, Freiburg, 2007.
• Neuronal tension may co-shape V1 orientation maps
  C Weber, J Triesch
  In: Proc. 31st Göttingen Neurobiology Conference, 2007.
• Intrinsic plasticity in a generative model of V1
  C Weber, J Triesch
  In: Proc. Dynamic Brain Forum, 2007.
• Learning to Attend - From Bottom-Up to Top-Down
  Jasso, H. & Triesch, J.
  In: Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint, Eds.: L. Paletta & E. Rome, Lecture Notes in Computer Science, 2007, Volume 4840/2007, 106-122, DOI: 10.1007/978-3-540-77343-6_7 
• Neural Control of Actions Involving Different Coordinate System
  C. Weber, M. Elshaw, J. Triesch, and S. Wermter.
  In: Humanoid Robots, Human-like Machines, I-Tech Education and Publishing, 2007. 
• Fire together - wire together - come together
  C Weber, J Triesch In: Proc. COSYNE, 2007
• Seizure induction by glia-mediated synaptic scaling
  C Savin, J Triesch, M Meyer-Hermann In: Proc. COSYNE, 2007
• Emergence of Disparity Tuning during the Development of Vergence Eye Movements
  A Franz and J Triesch
  Proc. Int. Conf. on Development and Learning (ICDL07).

2006

• Analysis of Cluttered Scenes Using an Elastic Matching Approach for Stereo Images
  C. Eckes, J. Triesch, and C. v.d. Malsburg
  Neural Computation 18:1441-1471, 2006.

• Modeling the Emergence of Gaze Following
  J. Triesch
  KI - Zeitschrift Künstliche Intelligenz, 2006.

• Gaze following: why (not) learn it?
  J. Triesch, C. Teuscher, G. Deak, and E. Carlson
  Developmental Science 9(2):125-147, 2006.

• Gaze following: how (not) to derive predictions from a computational model
  J. Triesch, C. Teuscher, G. Deak
  Developmental Science, 9(2):156-157, 2006.

• Change Blindness During Multiple Interactions With a Single Object
  A.E. Robinson, J. Triesch, M.M. Hayhoe, J.A. Droll, and B.T. Sullivan.
  Journal of Vision, Volume 6, Number 6, Abstract 986, Page 986a, doi:10.1167/6.6.986.

• Using Eye Direction Cues for Gaze Following - A Developmental Model
  H. Jasso and J. Triesch
  Proc. of the International Conference on Development and Learning (ICDL 2006).

• A reinforcement learning model explains the development of gaze following
  H. Jasso, J. Triesch, C. Teuscher, and G. Deak
  International Conference on Cognitive Modeling (ICCM2006), Trieste, Italy, April 5-8, 2006.

• Exploring the role of intrinsic plasticity for the learning of sensory representations
  N. Butko and J. Triesch
  European Symposium on Artificial Neural Networks (ESANN2006), Bruges, Belgium, April 26-28, 2006.

• The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks
  A. Lazar, G. Pipa, and J. Triesch
  European Symposium on Artificial Neural Networks (ESANN2006), Bruges, Belgium, April 26-28, 2006.

• A possible representation of reward in the learning of saccades
  C. Weber and J. Triesch
  Proc. Int. Conf. on Epigenetic Robotics (EPIROB06).

• Semi-Autonomous Learning of Objects
  H. Kim, E. Murphy-Chutorian, and J. Triesch
  Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2006).

• Emergence of Mirror Neurons in a Model of Gaze Following
  J. Triesch, H. Jasso, and G. Deak
  Proc. of the International Conference on Development and Learning (ICDL 2006).

• The emergence of attention-sharing skills in human infants
  Gedeon Deak and Jochen Triesch
  In: K. Fujita & S. Itakura (Eds.), Diversity of cognition. University of Kyoto Press.

2005

• Analysis of a biologically-inspired System for real-time object recognition
  E. Murphy-Chutorian, S. Aboutalib, and J. Triesch. 
  Cognitive Science Online, 3(2):1-14, 2005.
• Der simulierte Säugling (popular science article in german) 
  J Triesch
  Forschung Frankfurt, Issue 4/2005:62-64, 2005.
• Task Demands Control Acquisition and Maintenance of Visual Information J
  ason A. Droll, Mary M. Hayhoe, J. Triesch, and Brian T. Sullivan.
  J. Exp. Psychology: Human Perception and Performance 31(6):1416-1438, 2005.
• Learning Efficient Codes for Natural Images by Combining Intrinsic and Synaptic Plasticity
  J Triesch and N Butko
  Vision Science Society Meeting, VSS 2005
• The Costs of Visual Working Memory
  A. Robinson, A. Manzi, J. Triesch.
  Vision Science Society Meeting, VSS 2005
• A Unified Probabilistic Framework for Object Segmentation and Recognition
  H.-J. Chen, K.-C. Lee, E. Murphy-Chutorian, and J. Triesch.
  12th Joint Symposium on Neural Computation, JSNC 2005, Los Angeles, CA.
• A Reinforcement Learning Model Explains the Stage-wise Development of Gaze Following.
  H. Jasso, J. Triesch, C. Teuscher.
  12th Joint Symposium on Neural Computation, JSNC 2005, Los Angeles, CA.
• "A Virtual Reality Platform for Modeling Cognitive Development"
  H Jasso, J Triesch
  In: Lecture Notes in Computer Science, Volume 3575, Aug 2005, Pages 211 - 224. 
• Object Recognition with Deformable Feature Graphs: Faces, Hands, and Cluttered Scenes,
  J Triesch, C Eckes
  In: C.H. Chen (Ed.), Handbook of Pattern Recognition and Computer Vision, 3rd edition. World Scientific Publishing Co., 2005. 
• Toward a Unified Probabilistic Framework for Object Recognition and Segmentation
  H.-J. Chen, K.-C. Lee, E. Murphy-Chutorian, and J. Triesch
  Advances in Visual Computing: First International Symposium, ISVC 2005, Lake Tahoe, NV, USA, December 5-7, 2005.
• A Gradient Rule for the Plasticity of a Neuron's Intrinsic Excitability
  J. Triesch
  Int. Conf. on Artificial Neural Networks (ICANN 2005).
• Shared Features for Scalable Appearance-Based Object Recognition
  E. Murphy-Chutorian and J. Triesch
  IEEE Workshop on Applications of Computer Vision (WACV 2005).

2004

• Visual memory for natural scenes: automatic and task dependent components
  A Robinson and J Triesch.
  Vision Science Society Meeting, VSS 2004
• Working memory for object features is influenced by scene context
  J Droll, M Hayhoe, J Triesch, B Sullivan.
  Vision Science Society Meeting, VSS 2004
• Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons
  J Triesch
  Neural Information Processing Systems 17 (NIPS 2004)
• Learning gaze following in space: a computational model
  B Lau, J Triesch
  Proc. of the International Conference on Development and Learning (ICDL 2004)
• To Care or Not to Care: Analyzing the Caregiver in a Computational Gaze Following Framework
  C Teuscher, J Triesch
  Proc. of the International Conference on Development and Learning (ICDL 2004)
• A Virtual Reality Platform for Modeling Cognitive Development
  H Jasso, J Triesch
  Proc. of the International Conference on Development and Learning (ICDL 2004)
• Design of an Anthropomorphic Robot Head for Studying Development and Learning
  H Kim, G York, G Burton, E Murphy-Chutorian, J Triesch
  Proc. the of IEEE 2004 International Conference on Robotics and Automation (ICRA 2004)
• Adaptive Object Tracking with an Anthropomorphic Robot Head
  H Kim, B Lau, J Triesch
  8th Int. Conf. on the Simulation of Adaptive Behaviors (SAB'04)
• Hierarchical Sensor Data Fusion by Probabilistic Cue Integration for Robust 3-D Object Tracking
  O Kaehler, J Denzler, J Triesch
  Southwest Symposium on Image Analysis and Interpretation (SSIAI)

2003

• What you see is what you need
  J Triesch, DH Ballard, MM Hayhoe, and BT Sullivan
  Journal of Vision 3:86-94, 2003.

• Investigating the Emergence of Shared Attention through an Embodied Computational Modeling Approach: A Progress Report
  Conference Abstract  J Triesch, E Carlson, G Deak, and J Movellan
  Intl. Joint. Conf. on Neural Networks, IJCNN 2003.

• Task relevance of object features modulates the content of visual working memory
  J Droll, M Hayhoe, J Triesch, B Sullivan.
  Vision Science Society Meeting, VSS 2003.

• Learning Optimal Gaze Decomposition
  E Wiewiora, D Berg, J Triesch, and T Hashiyama.
  Vision Science Society Meeting, VSS 2003.
  

• A Computational Model of the Emergence of Gaze Following
  E Carlson and J Triesch
  Neural Computation and Psychology Workshop (NCPW8), Canterbury, UK, 2003

2002

• Fast temporal dynamics of visual cue integration
  J Triesch, DH Ballard, RA Jacobs
  Perception 31:421-434, 2002.

• Classification of Hand Postures Against Complex Backgrounds Using Elastic Graph Matching
  J Triesch, C von der Malsburg
  Image and Vision Computing, 20(13-14):937-943, 2002

• Probabilistic Integration of Cues from Multiple Cameras
  J Denzler, M Zobel, J Triesch
  4. Workshop Dynamic Perception, Bochum, Germany, 2002.

• Combining Embodied Models and Empirical Research for Understanding the Development of Shared Attention
  I Fasel, G Deak, J Triesch, J Movellan
  Proc. of the Intl. Conf. on Development and Learning (ICDL02), Boston, MA, USA, 2002.

• Saccade Contingent Updating in Virtual Reality
  J Triesch, B Sullivan, M Hayhoe, D Ballard
  Eye Tracking Research and Applications Symposium (ETRA), New Orleans, LA, USA, 2002.
  

• Vision in Natural and Virtual Evironments (2002)
  M Hayhoe, D Ballard, J Triesch, H Shinoda, P Aivar, B Sullivan
  Eye Tracking Research and Applications Symposium (ETRA), New Orleans, LA, USA, 2002.

2001

• A System for Person-Independent Hand Posture Recognition against Complex Backgrounds
  J Triesch, C von der Malsburg
  IEEE PAMI 23(12):1449-1453, 2001

• Democratic Integration: Self-Organized Integration of Adaptive Cues
  J Triesch, C von der Malsburg
  Neural Computation 13(9):2049-2074, 2001.

• Approaches and problems in the study and design of modular systems
  J Triesch
  Organic Computing Workshop, Paderborn, Germany, 2001.

• What you see is what you need
  J Triesch, DH Ballard, MH Hayhoe, and B Sullivan
  Society for Neuroscience Meeting, San Diego, California, 2001.

• Fast Temporal Dynamics of Visual Cue Integration
  J Triesch, DH Ballard and RA Jacobs
  Journal of Vision, 2001

• The role of a priori biases in unsupervised learning of visual representations: a robotics experiment
  J Triesch
  Developmental Embodied Cognition DECO-2001, Workshop at the University of Edinburgh, 31 July, 2001.

2000

• Self-Organized Integration of Adaptive Visual Cues for Face Tracking
  J Triesch
  In: Sensor Fusion: Architectures, Algorithms, and Applications IV, Belur V. Dasarathy, Editor, Proceedings of SPIE Vol. 4051, p. 397-406 (2000).

• Self-Organized Integration of Adaptive Visual Cues for Face Tracking (2000)
  J Triesch and C von der Malsburg
  In: Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2000), March 26-30 1998 in Grenoble, France, 2000

• Fast Temporal Dynamics of Visual Cue Integration
  J Triesch, DH Ballard and RA Jacobs
  National Resource Laboratory for the Study of Brain and Behavior, University of Rochester, Technical Report 00.2, September 2000.
• Democratic Integration: A Theory of Adaptive Sensory Integration
  J Triesch National Resource Laboratory for the Study of Brain and Behavior, University of Rochester, Technical Report 00.1, February 2000.

1999

• GripSee: A Gesture-controlled Robot for Object Perception and Manipulation
  M Becker, E Kefalea, E Maël, C von der Malsburg, M Pagel, J Triesch, JC Vorbrüggen, RP Würtz, S Zadel.
  Autonomous Robots 6(2):203-221, 1999.
• Vision-Based Robotic Gesture Recognition
  J Triesch
  Shaker Verlag, Aachen, Germany, ISBN 3-8265-6257-7,
  PhD thesis, Institut für Neuroinformatik, Ruhr-Universität Bochum, Germany, 1999
• Towards Imitation Learning of Grasping Movements by an Autonomous Robot
  J Triesch, J Wieghardt, E Maël, C von der Malsburg
  In: "Gesture-Based Communication in Human-Computer Interaction", Lecture Notes in Artificial Intelligence 1739: 73-84, Springer, 1999. 

1998

• Object Recognition with Multiple Feature Types
  J Triesch, C Eckes
  In: ICANN 98: International Conference on Artificial Neural Networks, September 2-4 1998, Skövde, Sweden, 1998.
• GripSee: A Robot for Visually-Guided Grasping
  M Becker, E Kefalea, E Maël, C von der Malsburg, M Pagel, J Triesch, JC Vorbrüggen, S Zadel
  In: ICANN 98: International Conference on Artificial Neural Networks, September 2-4 1998, Skövde, Sweden, 1998.
• A Gesture Interface for Human-Robot-Interaction
  J Triesch and C von der Malsburg
  In: Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition (FG'98), April 14-16 1998 in Nara, Japan.
• Robotic Gesture Recognition by Cue Combination
  J Triesch and C von der Malsburg
  In: J. Dassow and R. Kruse (eds.), "Informatik '98: Informatik zwischen Bild und Sprache", September 21-25, Magdeburg, Germany, 1998.
• The GripSee Project: A Gesture-controlled Robot for Learning and Using Object Representations 
  M Becker, E Kefalea, E Maël, C von der Malsburg, M Pagel, J Triesch, JC Vorbrüggen, RP Würtz, S Zadel
  Architectures in Cognitive Robotics, Report 98/13 of the SFB 360, University of Bielefeld, 1998.

1997

• Robotic Gesture Recognition
  J Triesch, C von der Malsburg
  In: "Gesture and Sign-Language in Human-Computer Interaction", Lecture Notes in Artificial Intelligence 1371: 233-244, Springer, 1997.

1996

• Binding - a proposed experiment and a model
  J Triesch, C von der Malsburg
  In: Proceedings of the International Conference on Artificial Neural Networks (ICANN), Bochum, Lecture Notes in Computer Science 1112, Springer, 1996.
• Robust Hand Posture Classification against Complex Backgrounds,
  J Triesch, C von der Malsburg
  In: Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, Killington, Vermont, USA, IEEE Computer Society Press, 1996.

1995

• Metrik im visuellen System (in German) (1995)
  J Triesch
  Master Thesis. Institut für Neuroinformatik., Ruhr-Universität Bochum, September 1994
  Published as Internal Report IRINI95-05 of the Institut für Neuroinformatik, Ruhr Universität Bochum