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Jochen Triesch
Person information
- affiliation: Goethe-Universität Frankfurt, Frankfurt am Main, Germany
- affiliation (former): University of California, San Diego, Department of Cognitive Science, USA
- affiliation (former): Ruhr-Universität Bochum, Germany
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2020 – today
- 2024
- [j43]Marius N. Vieth, Ali Rahimi, Ashena Gorgan Mohammadi, Jochen Triesch, Mohammad Ganjtabesh:
Accelerating spiking neural network simulations with PymoNNto and PymoNNtorch. Frontiers Neuroinformatics 18 (2024) - [j42]Dominik Mattern
, Pierre Schumacher
MIMo: A Multimodal Infant Model for Studying Cognitive Development. IEEE Trans. Cogn. Dev. Syst. 16(4): 1291-1301 (2024) - [c86]Arthur Aubret, Céline Teulière, Jochen Triesch:
Self-supervised Visual Learning from Interactions with Objects. ECCV (75) 2024: 54-71 - [c85]Arthur Aubret, Timothy Schaumlöffel, Gemma Roig, Jochen Triesch:
Learning Object Semantic Similarity with Self-Supervision. ICDL 2024: 1-6 - [c84]Markus Roland Ernst
Self-Supervised Learning of Color Constancy. ICDL 2024: 1-7 - [c83]Francisco M. López, Marcel C. Raabe, Bertram E. Shi
Self-Calibrating Saccade-Vergence Interactions. ICDL 2024: 1-7 - [i23]Markus Roland Ernst, Francisco M. López, Arthur Aubret, Roland W. Fleming, Jochen Triesch:
Self-Supervised Learning of Color Constancy. CoRR abs/2404.08127 (2024) - [i22]Arthur Aubret, Timothy Schaumlöffel, Gemma Roig, Jochen Triesch:
Learning Object Semantic Similarity with Self-Supervision. CoRR abs/2405.05143 (2024) - [i21]Arthur Aubret, Céline Teulière, Jochen Triesch:
Self-supervised visual learning from interactions with objects. CoRR abs/2407.06704 (2024) - 2023
- [j41]Marius Schneider
Biological complexity facilitates tuning of the neuronal parameter space. PLoS Comput. Biol. 19(7) (2023) - [j40]Kathryn Kasmarik
Guest Editorial Special Issue on Intrinsically Motivated Open-Ended Learning (IMOL). IEEE Trans. Cogn. Dev. Syst. 15(2): 321-324 (2023) - [j39]Charles Wilmot
Learning Abstract Representations Through Lossy Compression of Multimodal Signals. IEEE Trans. Cogn. Dev. Syst. 15(2): 348-360 (2023) - [j38]Emilio Cartoni
REAL-X - Robot Open-Ended Autonomous Learning Architecture: Building Truly End-to-End Sensorimotor Autonomous Learning Systems. IEEE Trans. Cogn. Dev. Syst. 15(4): 2014-2030 (2023) - [c82]Antony W. N'Dri, Thomas Barbier, Céline Teulière, Jochen Triesch:
Predictive Coding Light: learning compact visual codes by combining excitatory and inhibitory spike timing-dependent plasticity*. CVPR Workshops 2023: 3997-4006 - [c81]Zhengyang Yu, Jochen Triesch:
CRE: Circle relationship embedding of patches in vision transformer. ESANN 2023 - [c80]Diyuan Lu
Advancing Brain Tumor Detection with Multiple Instance Learning on Magnetic Resonance Spectroscopy Data. ICANN (4) 2023: 1-12 - [c79]Xia Xu, Jochen Triesch:
CIPER: Combining Invariant and Equivariant Representations Using Contrastive and Predictive Learning. ICANN (3) 2023: 320-331 - [c78]Timothy Schaumlöffel, Arthur Aubret, Gemma Roig, Jochen Triesch:
Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play. ICDL 2023: 67-72 - [c77]Marcel C. Raabe
Saccade Amplitude Statistics are Explained by Cortical Magnification. ICDL 2023: 300-305 - [c76]Francisco M. López, Bertram E. Shi
Eye-Hand Coordination Develops from Active Multimodal Compression. ICDL 2023: 437-442 - [c75]Arthur Aubret, Markus Roland Ernst
Time to augment self-supervised visual representation learning. ICLR 2023 - [i20]Xia Xu, Jochen Triesch:
CIPER: Combining Invariant and Equivariant Representations Using Contrastive and Predictive Learning. CoRR abs/2302.02330 (2023) - [i19]Timothy Schaumlöffel, Arthur Aubret, Gemma Roig, Jochen Triesch:
Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play. CoRR abs/2312.04118 (2023) - [i18]Dominik Mattern, Pierre Schumacher, Francisco M. López, Marcel C. Raabe, Markus Roland Ernst, Arthur Aubret, Jochen Triesch:
MIMo: A Multi-Modal Infant Model for Studying Cognitive Development. CoRR abs/2312.04318 (2023) - 2022
- [j37]Qingpeng Zhu
Learning torsional eye movements through active efficient coding. Neuromorph. Comput. Eng. 2(3): 34007 (2022) - [c74]Dominik Mattern, Francisco M. López, Markus Roland Ernst
MIMo: A Multi-Modal Infant Model for Studying Cognitive Development in Humans and AIs. ICDL 2022: 23-29 - [c73]Arthur Aubret, Céline Teulière, Jochen Triesch:
Toddler-inspired embodied vision for learning object representations. ICDL 2022: 81-87 - [c72]Amr Farahat, Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
Diagnosing Epileptogenesis with Deep Anomaly Detection. MLHC 2022: 325-342 - [i17]Arthur Aubret, Céline Teulière, Jochen Triesch:
Embodied vision for learning object representations. CoRR abs/2205.06198 (2022) - [i16]Arthur Aubret, Markus Roland Ernst, Céline Teulière, Jochen Triesch:
Time to augment contrastive learning. CoRR abs/2207.13492 (2022) - [i15]Zhengyang Yu, Jochen Triesch:
Sequence and Circle: Exploring the Relationship Between Patches. CoRR abs/2210.09871 (2022) - 2021
- [j36]Marius N. Vieth, Tristan M. Stöber
PymoNNto: A Flexible Modular Toolbox for Designing Brain-Inspired Neural Networks. Frontiers Neuroinformatics 15: 715131 (2021) - [j35]Frederic von Wegner
EEG microstate periodicity explained by rotating phase patterns of resting-state alpha oscillations. NeuroImage 224: 117372 (2021) - [j34]Lakshitha P. Wijesinghe
Active head rolls enhance sonar-based auditory localization performance. PLoS Comput. Biol. 17(5) (2021) - [c71]Thomas Barbier, Céline Teulière, Jochen Triesch:
Spike Timing-Based Unsupervised Learning of Orientation, Disparity, and Motion Representations in a Spiking Neural Network. CVPR Workshops 2021: 1377-1386 - [c70]Norman Seeliger, Jochen Triesch:
A Computational Model of the Effect of Short-Term Monocular Deprivation on Binocular Rivalry in the Context of Amblyopia. ICANN (1) 2021: 593-603 - [c69]Diyuan Lu, Nenad Polomac, Iskra Gacheva, Elke Hattingen
Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation And Augmentation. ICASSP 2021: 3975-3979 - [i14]Charles Wilmot, Jochen Triesch:
Learning Abstract Representations through Lossy Compression of Multi-Modal Signals. CoRR abs/2101.11376 (2021) - [i13]Charles Wilmot, Bertram E. Shi, Jochen Triesch:
Self-Calibrating Active Binocular Vision via Active Efficient Coding with Deep Autoencoders. CoRR abs/2101.11391 (2021) - [i12]Zhetuo Zhao, Jochen Triesch, Bertram E. Shi:
Learning Hierarchical Integration of Foveal and Peripheral Vision for Vergence Control by Active Efficient Coding. CoRR abs/2103.05100 (2021) - [i11]Markus Roland Ernst, Jochen Triesch, Thomas Burwick:
Recurrent Feedback Improves Recognition of Partially Occluded Objects. CoRR abs/2104.10615 (2021) - [i10]Diyuan Lu, Gerhard Kurz, Nenad Polomac, Iskra Gacheva, Elke Hattingen, Jochen Triesch:
Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data. CoRR abs/2112.08845 (2021) - 2020
- [j33]Qingpeng Zhu
An Event-by-Event Approach for Velocity Estimation and Object Tracking With an Active Event Camera. IEEE J. Emerg. Sel. Topics Circuits Syst. 10(4): 557-566 (2020) - [c68]Qingpeng Zhu, Jochen Triesch, Bertram E. Shi
Retinal Slip Estimation and Object Tracking with an Active Event Camera. AICAS 2020: 59-63 - [c67]Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
Staging Epileptogenesis with Deep Neural Networks. BCB 2020: 60:1-60:10 - [c66]Markus Roland Ernst, Jochen Triesch, Thomas Burwick:
Recurrent Feedback Improves Recognition of Partially Occluded Objects. ESANN 2020: 327-332 - [c65]Thomas Barbier
Unsupervised Learning of Spatio-Temporal Receptive Fields from an Event-Based Vision Sensor. ICANN (2) 2020: 622-633 - [c64]Charles Wilmot, Bertram E. Shi
Self-Calibrating Active Binocular Vision via Active Efficient Coding with Deep Autoencoders. ICDL-EPIROB 2020: 1-6 - [c63]Qingpeng Zhu, Jochen Triesch, Bertram E. Shi
Integration of Vergence, Cyclovergence, and Saccades through Active Efficient Coding. ICDL-EPIROB 2020: 1-6 - [c62]Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
Towards Early Diagnosis of Epilepsy from EEG Data. MLHC 2020: 80-96 - [i9]Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
Towards Early Diagnosis of Epilepsy from EEG Data. CoRR abs/2006.06675 (2020) - [i8]Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
Staging Epileptogenesis with Deep Neural Networks. CoRR abs/2006.09885 (2020) - [i7]Diyuan Lu, Nenad Polomac, Iskra Gacheva, Elke Hattingen, Jochen Triesch:
Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation. CoRR abs/2006.12285 (2020) - [i6]Emilio Cartoni
An open-ended learning architecture to face the REAL 2020 simulated robot competition. CoRR abs/2011.13880 (2020)
2010 – 2019
- 2019
- [j32]Alexander Lelais
Autonomous Development of Active Binocular and Motion Vision Through Active Efficient Coding. Frontiers Neurorobotics 13: 49 (2019) - [c61]Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch:
A Deep Residual Neural Network Based Framework for Epileptogenesis Detection in a Rodent Model with Single-Channel EEG Recordings. CISP-BMEI 2019: 1-6 - [c60]Markus Roland Ernst
Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders. ICANN (3) 2019: 294-305 - [c59]François De La Bourdonnaye, Céline Teulière, Thierry Chateau, Jochen Triesch:
Within Reach? Learning to touch objects without prior models. ICDL-EPIROB 2019: 93-98 - [c58]Emilio Cartoni, Francesco Mannella, Vieri Giuliano Santucci
REAL-2019: Robot open-Ended Autonomous Learning competition. NeurIPS (Competition and Demos) 2019: 142-152 - [i5]Diyuan Lu, Jochen Triesch:
Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy. CoRR abs/1903.08100 (2019) - [i4]Markus Roland Ernst, Jochen Triesch, Thomas Burwick:
Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders. CoRR abs/1907.08831 (2019) - [i3]Markus Roland Ernst, Jochen Triesch, Thomas Burwick:
Recurrent Connectivity Aids Recognition of Partly Occluded Objects. CoRR abs/1909.06175 (2019) - 2018
- [j31]Lakshitha P. Wijesinghe, Jochen Triesch, Bertram E. Shi
Robot End Effector Tracking Using Predictive Multisensory Integration. Frontiers Neurorobotics 12: 66 (2018) - [j30]François De La Bourdonnaye, Céline Teulière, Jochen Triesch, Thierry Chateau:
Stage-Wise Learning of Reaching Using Little Prior Knowledge. Frontiers Robotics AI 5: 110 (2018) - [j29]Christian Klos
Bridging structure and function: A model of sequence learning and prediction in primary visual cortex. PLoS Comput. Biol. 14(6) (2018) - [c57]Qingpeng Zhu, Chong Zhang, Jochen Triesch, Bertram E. Shi
Autonomous learning of cyclovergence control based on Active Efficient Coding. ICDL-EPIROB 2018: 251-256 - [c56]François De La Bourdonnaye, Céline Teulière, Jochen Triesch, Thierry Chateau:
Learning to Touch Objects Through Stage-Wise Deep Reinforcement Learning. IROS 2018: 1-9 - [c55]Lukas Klimmasch, Johann Schneider, Alexander Lelais
An Active Efficient Coding Model of Binocular Vision Development Under Normal and Abnormal Rearing Conditions. SAB 2018: 66-77 - [c54]Zhetuo Zhao, Jochen Triesch, Bertram E. Shi
Learning Hierarchical Integration of Foveal and Peripheral Vision for Vergence Control by Active Efficient Coding. SAB 2018: 78-89 - [e1]Poramate Manoonpong, Jørgen Christian Larsen
From Animals to Animats 15 - 15th International Conference on Simulation of Adaptive Behavior, SAB 2018, Frankfurt/Main, Germany, August 14-17, 2018, Proceedings. Lecture Notes in Computer Science 10994, Springer 2018, ISBN 978-3-319-97627-3 [contents] - 2017
- [j28]Qingpeng Zhu
Joint Learning of Binocularly Driven Saccades and Vergence by Active Efficient Coding. Frontiers Neurorobotics 11: 58 (2017) - [j27]Quan Wang
A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity. PLoS Comput. Biol. 13(8) (2017) - [c53]Lukas Klimmasch, Alexander Lelais
Learning of active binocular vision in a biomechanical model of the oculomotor system. ICDL-EPIROB 2017: 21-26 - [c52]Qingpeng Zhu
Autonomous, self-calibrating binocular vision based on learned attention and active efficient coding. ICDL-EPIROB 2017: 27-32 - [c51]Chong Zhang, Jochen Triesch, Bertram E. Shi
Learning multisensory cue integration on mobile robots. ICRA 2017: 3546-3551 - [c50]François De La Bourdonnaye, Céline Teulière, Thierry Chateau, Jochen Triesch:
Learning of binocular fixations using anomaly detection with deep reinforcement learning. IJCNN 2017: 760-767 - [c49]Lakshitha P. Wijesinghe, Marco Antonelli, Jochen Triesch, Bertram E. Shi
Learning multisensory neural controllers for robot arm tracking. IJCNN 2017: 4150-4157 - 2016
- [j26]Daniel Miner, Jochen Triesch:
Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring. PLoS Comput. Biol. 12(2) (2016) - [c48]Tanapol Prucksakorn, Sungmoon Jeong, Jochen Triesch, Hosun Lee, Nak Young Chong
Self-calibrating active depth perception via motion parallax. ICDL-EPIROB 2016: 103-108 - [c47]Alexa R. Romberg, Yayun Zhang, Benjamin Newman, Jochen Triesch, Chen Yu:
Global and local statistical regularities control visual attention to object sequences. ICDL-EPIROB 2016: 262-267 - [c46]Max Murakami, Jantina Bolhuis, Thorsten Kolling, Monika Knopf, Jochen Triesch:
Look and learn: A model of gaze-contingent learning. ICDL-EPIROB 2016: 284-285 - [i2]Chong Zhang, Jochen Triesch, Bertram E. Shi:
An active efficient coding model of the optokinetic nystagmus. CoRR abs/1606.06443 (2016) - 2015
- [j25]Christoph Hartmann, Andreea Lazar, Bernhard Nessler, Jochen Triesch:
Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network. PLoS Comput. Biol. 11(12) (2015) - [j24]Céline Teulière, Sébastien Forestier, Luca Lonini, Chong Zhang, Yu Zhao, Bertram E. Shi
Self-calibrating smooth pursuit through active efficient coding. Robotics Auton. Syst. 71: 3-12 (2015) - [c45]Kishore Konda, Pramod Chandrashekhariah, Roland Memisevic, Jochen Triesch:
Real-time activity recognition via deep learning of motion features. ESANN 2015 - [c44]Alexander Priamikov, Vikram Narayan, Bertram E. Shi
The role of contrast sensitivity in the development of binocular vision: A computational study. ICDL-EPIROB 2015: 33-38 - [c43]Thusitha N. Chandrapala, Bertram E. Shi
Active maintenance of binocular correspondence leads to orientation alignment of visual receptive fields. ICDL-EPIROB 2015: 98-103 - [c42]Max Murakami, Bernd J. Kröger, Peter Birkholz
Seeing [u] aids vocal learning: Babbling and imitation of vowels using a 3D vocal tract model, reinforcement learning, and reservoir computing. ICDL-EPIROB 2015: 208-213 - [c41]Thusitha N. Chandrapala, Bertram E. Shi
On the utility of sparse neural representations in adaptive behaving agents. IJCNN 2015: 1-8 - 2014
- [j23]Cristina Savin
Emergence of task-dependent representations in working memory circuits. Frontiers Comput. Neurosci. 8: 57 (2014) - [j22]Pengsheng Zheng, Jochen Triesch:
Robust development of synfire chains from multiple plasticity mechanisms. Frontiers Comput. Neurosci. 8: 66 (2014) - [c40]Alexander Priamikov, Jochen Triesch:
OpenEyeSim - A platform for biomechanical modeling of oculomotor control. ICDL-EPIROB 2014: 394-395 - [c39]T. N. Vikram, Céline Teulière, Chong Zhang
Autonomous learning of smooth pursuit and vergence through active efficient coding. ICDL-EPIROB 2014: 448-453 - [c38]Chong Zhang
Intrinsically motivated learning of visual motion perception and smooth pursuit. ICRA 2014: 1902-1908 - [c37]Pramod Chandrashekhariah, Jochen Triesch:
Hide and Seek - An Active Binocular Object Tracking System. VISAPP (3) 2014: 584-591 - [r1]Jochen Triesch:
Cortical Function, Normative Models of. Encyclopedia of Computational Neuroscience 2014 - [i1]Chong Zhang, Yu Zhao, Jochen Triesch, Bertram E. Shi:
Intrinsically Motivated Learning of Visual Motion Perception and Smooth Pursuit. CoRR abs/1402.3344 (2014) - 2013
- [j21]Luca Lonini, Sébastien Forestier, Céline Teulière, Yu Zhao, Bertram E. Shi
Robust active binocular vision through intrinsically motivated learning. Frontiers Neurorobotics 7: 20 (2013) - [j20]Pengsheng Zheng, Christos Dimitrakakis
Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex. PLoS Comput. Biol. 9(1) (2013) - [c36]Luca Lonini, Yu Zhao, Pramod Chandrashekhariah, Bertram E. Shi
Autonomous learning of active multi-scale binocular vision. ICDL-EPIROB 2013: 1-6 - [c35]Pramod Chandrashekhariah, Gabriele Spina, Jochen Triesch:
Let it Learn - A Curious Vision System for Autonomous Object Learning. VISAPP (2) 2013: 169-176 - [c34]Pramod Chandrashekhariah, Gabriele Spina
A Curious Vision System for Autonomous and Cumulative Object Learning. VISIGRAPP (Selected Papers) 2013: 195-211 - [p1]Luca Lonini, Christos Dimitrakakis
Generalization and Interference in Human Motor Control. Computational and Robotic Models of the Hierarchical Organization of Behavior 2013: 155-176 - 2012
- [j19]Hector Jasso, Jochen Triesch, Gedeon O. Deák
A Unified Account of Gaze Following. IEEE Trans. Auton. Ment. Dev. 4(4): 257-272 (2012) - [c33]Jürgen Leitner
Autonomous learning of robust visual object detection and identification on a humanoid. ICDL-EPIROB 2012: 1-6 - [c32]Rodolfo Marraffa, Valerio Sperati
A bio-inspired attention model of anticipation in gaze-contingency experiments with infants. ICDL-EPIROB 2012: 1-8 - [c31]Yu Zhao, Constantin A. Rothkopf
A unified model of the joint development of disparity selectivity and vergence control. ICDL-EPIROB 2012: 1-6 - 2011
- [j18]Sohrab Saeb, Cornelius Weber, Jochen Triesch:
Learning the Optimal Control of Coordinated Eye and Head Movements. PLoS Comput. Biol. 7(11) (2011) - [j17]Angelo Cangelosi
From Infant Brains to Robots: A Report From the IEEE International Conference on Development and Learning (ICDL)-International Conference on Epigenetic Robotics (EpiRob) 2011 Conference. IEEE Trans. Auton. Ment. Dev. 3(4): 276 (2011) - [c30]Andreea Lazar, Gordon Pipa, Jochen Triesch:
Emerging Bayesian Priors in a Self-Organizing Recurrent Network. ICANN (2) 2011: 127-134 - [c29]Hazem Toutounji
Scalable reinforcement learning through hierarchical decompositions for weakly-coupled problems. ICDL-EPIROB 2011: 1-7 - 2010
- [j16]Cristina Savin
Independent Component Analysis in Spiking Neurons. PLoS Comput. Biol. 6(4) (2010)
2000 – 2009
- 2009
- [j15]Andreea Lazar, Gordon Pipa, Jochen Triesch:
SORN: a self-organizing recurrent neural network. Frontiers Comput. Neurosci. 3: 23 (2009) - [j14]Sohrab Saeb, Cornelius Weber, Jochen Triesch:
Goal-directed learning of features and forward models. Neural Networks 22(5-6): 586-592 (2009) - [j13]Jochen Triesch, Zhengyou Zhang:
Report on the IEEE 8th International Conference on Development and Learning (ICDL-2009). IEEE Trans. Auton. Ment. Dev. 1(3): 154 (2009) - [c28]Felipe Gerhard, Cristina Savin, Jochen Triesch:
A robust biologically plausible implementation of ICA-like learning. ESANN 2009 - [c27]Prashant Joshi, Jochen Triesch:
Optimizing Generic Neural Microcircuits through Reward Modulated STDP. ICANN (1) 2009: 239-248 - [c26]Prashant Joshi, Jochen Triesch:
Rules for information maximization in spiking neurons using intrinsic plasticity. IJCNN 2009: 1456-1461 - [c25]Sohrab Saeb, Cornelius Weber, Jochen Triesch:
A neural model for the adaptive control of saccadic eye movements. IJCNN 2009: 2740-2747 - [c24]Cornelius Weber, Jochen Triesch:
Goal-directed feature learning. IJCNN 2009: 3319-3326 - 2008
- [j12]Cornelius Weber, Jochen Triesch:
A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity. Neural Comput. 20(5): 1261-1284 (2008) - [c23]Kai Willadsen, Jochen Triesch, Janet Wiles:
Understanding robustness in Random Boolean Networks. ALIFE 2008: 694-701 - [c22]Andreea Lazar, Gordon Pipa, Jochen Triesch:
Predictive Coding in Cortical Microcircuits. ICANN (2) 2008: 386-395 - [c21]Prashant Joshi, Jochen Triesch:
A Globally Asymptotically Stable Plasticity Rule for Firing Rate Homeostasis. ICANN (2) 2008: 567-576 - [c20]Cornelius Weber, Jochen Triesch:
From Exploration to Planning. ICANN (1) 2008: 740-749 - 2007
- [j11]Jochen Triesch, Hector Jasso, Gedeon O. Deák
Emergence of Mirror Neurons in a Model of Gaze Following. Adapt. Behav. 15(2): 149-165 (2007) - [j10]Nicholas Butko, Jochen Triesch:
Learning sensory representations with intrinsic plasticity. Neurocomputing 70(7-9): 1130-1138 (2007) - [j9]Christof Teuscher, Jochen Triesch:
To each his own: The caregiver's role in a computational model of gaze following. Neurocomputing 70(13-15): 2166-2180 (2007) - [j8]Jochen Triesch:
Synergies Between Intrinsic and Synaptic Plasticity Mechanisms. Neural Comput. 19(4): 885-909 (2007) - [j7]Andreea Lazar, Gordon Pipa, Jochen Triesch:
Fading memory and time series prediction in recurrent networks with different forms of plasticity. Neural Networks 20(3): 312-322 (2007) - [c19]Hector Jasso, Jochen Triesch:
Learning to Attend - From Bottom-Up to Top-Down. WAPCV 2007: 106-122 - 2006
- [j6]Jochen Triesch:
Modeling the emergence of gaze following. Künstliche Intell. 20(3): 27-30 (2006) - [j5]Christian Eckes, Jochen Triesch, Christoph von der Malsburg:
Analysis of Cluttered Scenes Using an Elastic Matching Approach for Stereo Images. Neural Comput. 18(6): 1441-1471 (2006) - [c18]Hyundo Kim, Erik Murphy-Chutorian, Jochen Triesch:
Semi-autonomous Learning of Objects. CVPR Workshops 2006: 145 - [c17]Nicholas Butko, Jochen Triesch:
Exploring the role of intrinsic plasticity for the learning of sensory representations. ESANN 2006: 467-472 - [c16]Andreea Lazar, Gordon Pipa, Jochen Triesch:
The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks. ESANN 2006: 647-652 - 2005
- [c15]Jochen Triesch:
A Gradient Rule for the Plasticity of a Neuron's Intrinsic Excitability. ICANN (1) 2005: 65-70 - [c14]Huei-Ju Chen, Kuang-Chih Lee, Erik Murphy-Chutorian, Jochen Triesch:
Toward a Unified Probabilistic Framework for Object Recognition and Segmentation. ISVC 2005: 108-117 - [c13]Hector Jasso, Jochen Triesch:
A Virtual Reality Platform for Modeling Cognitive Development. Biomimetic Neural Learning for Intelligent Robots 2005: 211-224 - [c12]Erik Murphy-Chutorian, Jochen Triesch:
Shared Features for Scalable Appearance-Based Object Recognition. WACV/MOTION 2005: 16-21 - 2004
- [c11]Hyundo Kim, George York, Greg Burton, Erik Murphy-Chutorian, Jochen Triesch:
Design of an Anthropomorphic Robot Head for Studying Autonomous Development and Learning. ICRA 2004: 3506-3511 - [c10]Jochen Triesch:
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons. NIPS 2004: 1417-1424 - 2002
- [j4]Jochen Triesch, Christoph von der Malsburg:
Classification of hand postures against complex backgrounds using elastic graph matching. Image Vis. Comput. 20(13-14): 937-943 (2002) - [c9]Mary M. Hayhoe, Dana H. Ballard, Jochen Triesch, Hiroyuki Shinoda, Pilar Aivar
Vision in natural and virtual environments. ETRA 2002: 7-13 - [c8]Jochen Triesch, Brian T. Sullivan, Mary M. Hayhoe, Dana H. Ballard:
Saccade contingent updating in virtual reality. ETRA 2002: 95-102 - 2001
- [j3]Jochen Triesch, Christoph von der Malsburg:
Democratic Integration: Self-Organized Integration of Adaptive Cues. Neural Comput. 13(9): 2049-2074 (2001) - [j2]Jochen Triesch, Christoph von der Malsburg:
A System for Person-Independent Hand Posture Recognition against Complex Backgrounds. IEEE Trans. Pattern Anal. Mach. Intell. 23(12): 1449-1453 (2001) - 2000
- [c7]Jochen Triesch, Christoph von der Malsburg:
Self-Organized Integration of Adaptive Visual Cues for Face Tracking. FG 2000: 102-109
1990 – 1999
- 1999
- [b1]Jochen Triesch:
Vision based robotic gesture recognition. Ruhr University Bochum, Germany, Shaker 1999, ISBN 978-3-8265-6257-0, pp. 1-116 - [j1]Mark Becker, Efthimia Kefalea, Eric Maël, Christoph von der Malsburg, Mike Pagel, Jochen Triesch, Jan C. Vorbrüggen, Rolf P. Würtz
GripSee: A Gesture-Controlled Robot for Object Perception and Manipulation. Auton. Robots 6(2): 203-221 (1999) - [c6]Jochen Triesch, Jan Wieghardt, Eric Maël, Christoph von der Malsburg:
Towards Imitation Learning of Grasping Movements by an Autonomous Robot. Gesture Workshop 1999: 73-84 - 1998
- [c5]Jochen Triesch, Christoph von der Malsburg:
A Gesture Interface for Human-Robot-Interaction. FG 1998: 546-551 - [c4]Jochen Triesch, Christoph von der Malsburg:
Robotic Gesture Recognition by Cue Combination. GI Jahrestagung 1998: 223-232 - 1997
- [c3]Jochen Triesch, Christoph von der Malsburg:
Robotic Gesture Recognition. Gesture Workshop 1997: 233-244 - 1996
- [c2]Jochen Triesch, Christoph von der Malsburg:
Robust classification of hand postures against complex backgrounds. FG 1996: 170-175 - [c1]Jochen Triesch, Christoph von der Malsburg:
Binding - A Proposed Experiment and a Model. ICANN 1996: 685-690
Coauthor Index
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