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Cornelius Weber - Publications

Affiliations: 
Frankfurt Institute for Advanced Studies, Fijaš, Slovakia 
Website:
http://fias.uni-frankfurt.de/~cweber/
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37 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2022 Lee JH, Yao Y, Özdemir O, Li M, Weber C, Liu Z, Wermter S. Spatial relation learning in complementary scenarios with deep neural networks. Frontiers in Neurorobotics. 16: 844753. PMID 35966371 DOI: 10.3389/fnbot.2022.844753  0.329
2020 Fu D, Weber C, Yang G, Kerzel M, Nan W, Barros P, Wu H, Liu X, Wermter S. What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective. Frontiers in Integrative Neuroscience. 14: 10. PMID 32174816 DOI: 10.3389/Fnint.2020.00010  0.346
2020 Xie R, Heinrich S, Liu Z, Weber C, Yao Y, Wermter S, Sun M. Integrating Image-Based and Knowledge-Based Representation Learning Ieee Transactions On Cognitive and Developmental Systems. 12: 169-178. DOI: 10.1109/Tcds.2019.2906685  0.405
2019 Mao J, Yao Y, Heinrich S, Hinz T, Weber C, Wermter S, Liu Z, Sun M. Bootstrapping Knowledge Graphs From Images and Text. Frontiers in Neurorobotics. 13: 93. PMID 31798437 DOI: 10.3389/Fnbot.2019.00093  0.313
2019 Hafez MB, Weber C, Kerzel M, Wermter S. Deep intrinsically motivated continuous actor-critic for efficient robotic visuomotor skill learning Paladyn, Journal of Behavioral Robotics. 10: 14-29. DOI: 10.1515/pjbr-2019-0005  0.393
2018 Parisi GI, Tani J, Weber C, Wermter S. Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-Organization. Frontiers in Neurorobotics. 12: 78. PMID 30546302 DOI: 10.3389/fnbot.2018.00078  0.334
2018 Zamani MA, Magg S, Weber C, Wermter S, Fu D. Deep reinforcement learning using compositional representations for performing instructions Paladyn, Journal of Behavioral Robotics. 9: 358-373. DOI: 10.1515/pjbr-2018-0026  0.36
2017 Parisi GI, Tani J, Weber C, Wermter S. Lifelong learning of human actions with deep neural network self-organization. Neural Networks : the Official Journal of the International Neural Network Society. 96: 137-149. PMID 29017140 DOI: 10.1016/j.neunet.2017.09.001  0.402
2017 Barros P, Parisi GI, Weber C, Wermter S. Emotion-modulated attention improves expression recognition: A deep learning model Neurocomputing. 253: 104-114. DOI: 10.1016/J.Neucom.2017.01.096  0.364
2017 Tsironi E, Barros P, Weber C, Wermter S. An analysis of Convolutional Long Short-Term Memory Recurrent Neural Networks for gesture recognition Neurocomputing. 268: 76-86. DOI: 10.1016/J.Neucom.2016.12.088  0.411
2017 Parisi GI, Tani J, Weber C, Wermter S. Emergence of multimodal action representations from neural network self-organization Cognitive Systems Research. 43: 208-221. DOI: 10.1016/J.Cogsys.2016.08.002  0.456
2016 Cruz F, Magg S, Weber C, Wermter S. Training Agents With Interactive Reinforcement Learning and Contextual Affordances Ieee Transactions On Cognitive and Developmental Systems. 8: 271-284. DOI: 10.1109/Tcds.2016.2543839  0.434
2015 Barros P, Jirak D, Weber C, Wermter S. Multimodal emotional state recognition using sequence-dependent deep hierarchical features. Neural Networks : the Official Journal of the International Neural Network Society. PMID 26548943 DOI: 10.1016/J.Neunet.2015.09.009  0.32
2015 Parisi GI, Weber C, Wermter S. Self-organizing neural integration of pose-motion features for human action recognition. Frontiers in Neurorobotics. 9: 3. PMID 26106323 DOI: 10.3389/Fnbot.2015.00003  0.42
2013 Yan W, Weber C, Wermter S. Learning indoor robot navigation using visual and sensorimotor map information. Frontiers in Neurorobotics. 7: 15. PMID 24109451 DOI: 10.3389/Fnbot.2013.00015  0.43
2012 Zhong J, Weber C, Wermter S. A Predictive Network Architecture for a Robust and Smooth Robot Docking Behavior Paladyn, Journal of Behavioral Robotics. 3. DOI: 10.2478/S13230-013-0106-8  0.428
2012 Navarro-Guerrero N, Weber C, Schroeter P, Wermter S. Real-world reinforcement learning for autonomous humanoid robot docking Robotics and Autonomous Systems. 60: 1400-1407. DOI: 10.1016/J.Robot.2012.05.019  0.454
2012 Heinrich S, Weber C, Wermter S. Adaptive learning of linguistic hierarchy in a multiple timescale recurrent neural network Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7552: 555-562. DOI: 10.1007/978-3-642-33269-2_70  0.306
2011 Saeb S, Weber C, Triesch J. Learning the optimal control of coordinated eye and head movements. Plos Computational Biology. 7: e1002253. PMID 22072953 DOI: 10.1371/Journal.Pcbi.1002253  0.569
2011 Kleesiek J, Engel AK, Weber C, Wermter S. Reward-driven learning of sensorimotor laws and visual features 2011 Ieee International Conference On Development and Learning, Icdl 2011. DOI: 10.1109/DEVLRN.2011.6037358  0.313
2009 Saeb S, Weber C, Triesch J. Goal-directed learning of features and forward models. Neural Networks : the Official Journal of the International Neural Network Society. 22: 586-92. PMID 19616917 DOI: 10.1016/J.Neunet.2009.06.049  0.601
2009 Weber C, Triesch J. Implementations and implications of foveated vision Recent Patents On Computer Science. 2: 75-85. DOI: 10.2174/1874479600902010075  0.553
2009 Weber C, Triesch J. Goal-directed feature learning Proceedings of the International Joint Conference On Neural Networks. 3319-3326. DOI: 10.1109/IJCNN.2009.5179064  0.546
2009 Saeb S, Weber C, Triesch J. A neural model for the adaptive control of saccadic eye movements Proceedings of the International Joint Conference On Neural Networks. 2740-2747. DOI: 10.1109/IJCNN.2009.5178878  0.509
2008 Weber C. How do we approach intrinsic motivation computationally. Frontiers in Neurorobotics. 2. PMID 20827402 DOI: 10.3389/Neuro.12.001.2008  0.434
2008 Weber C, Triesch J. A sparse generative model of V1 simple cells with intrinsic plasticity. Neural Computation. 20: 1261-84. PMID 18194109 DOI: 10.1162/Neco.2007.02-07-472  0.564
2008 Weber C, Triesch J. From exploration to planning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5163: 740-749. DOI: 10.1007/978-3-540-87536-9_76  0.428
2007 Weber C, Wermter S. A self-organizing map of sigma-pi units Neurocomputing. 70: 2552-2560. DOI: 10.1016/J.Neucom.2006.05.014  0.352
2006 Weber C, Wermter S, Elshaw M. A hybrid generative and predictive model of the motor cortex. Neural Networks : the Official Journal of the International Neural Network Society. 19: 339-53. PMID 16352416 DOI: 10.1016/J.Neunet.2005.10.004  0.349
2006 Weber C, Muse D, Elshaw M, Wermter S. A camera-direction dependent visual-motor coordinate transformation for a visually guided neural robot Knowledge-Based Systems. 19: 348-355. DOI: 10.1016/J.Knosys.2005.11.020  0.379
2006 Muse D, Weber C, Wermter S. Robot docking based on omnidirectional vision and reinforcement learning Knowledge-Based Systems. 19: 324-332. DOI: 10.1016/J.Knosys.2005.11.018  0.386
2005 Wermter S, Weber C, Elshaw M, Gallese V, Pulvermüller F. Grounding neural robot language in action Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3575: 162-181. DOI: 10.1007/11521082_10  0.399
2005 Wermter S, Palm G, Weber C, Elshaw M. Towards biomimetic neural learning for intelligent robots Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3575: 1-18. DOI: 10.1007/11521082_1  0.452
2004 Wermter S, Weber C, Elshaw M, Panchev C, Erwin H, Pulverm̈uller F. Towards multimodal neural robot learning Robotics and Autonomous Systems. 47: 171-175. DOI: 10.1016/J.Robot.2004.03.011  0.461
2004 Weber C, Wermter S, Zochios A. Robot docking with neural vision and reinforcement Knowledge-Based Systems. 17: 165-172. DOI: 10.1016/J.Knosys.2004.03.012  0.399
2001 Weber C, Obermayer K. Emergence of Modularity within One Sheet of Neurons: A Model Comparison Lecture Notes in Computer Science. 53-67. DOI: 10.1007/3-540-44597-8_4  0.546
1997 Weber C. Development and regeneration of the retinotectal map in goldfish: A computational study Philosophical Transactions of the Royal Society B: Biological Sciences. 352: 1603-1623. DOI: 10.1098/Rstb.1997.0144  0.326
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