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Joel Z. Leibo
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2020 – today
- 2024
- [j12]Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck:
Resolving social dilemmas with minimal reward transfer. Auton. Agents Multi Agent Syst. 38(2): 49 (2024) - [c30]Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess:
Neural Population Learning beyond Symmetric Zero-Sum Games. AAMAS 2024: 1247-1255 - [i63]Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess:
Neural Population Learning beyond Symmetric Zero-sum Games. CoRR abs/2401.05133 (2024) - [i62]Luke Marris, Ian Gemp, Siqi Liu, Joel Z. Leibo, Georgios Piliouras:
Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package. CoRR abs/2402.16985 (2024) - [i61]Edgar A. Duéñez-Guzmán, Suzanne Sadedin, Jane X. Wang, Kevin R. McKee, Joel Z. Leibo:
A social path to human-like artificial intelligence. CoRR abs/2405.15815 (2024) - [i60]Jonathan Cook, Chris Lu, Edward Hughes, Joel Z. Leibo, Jakob N. Foerster:
Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning. CoRR abs/2406.00392 (2024) - 2023
- [j11]Madeline G. Reinecke, Yiran Mao, Markus Kunesch, Edgar A. Duéñez-Guzmán
, Julia Haas, Joel Z. Leibo:
The Puzzle of Evaluating Moral Cognition in Artificial Agents. Cogn. Sci. 47(8) (2023) - [j10]Edgar A. Duéñez-Guzmán
A social path to human-like artificial intelligence. Nat. Mac. Intell. 5(11): 1181-1188 (2023) - [c29]Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Igor Mordatch, Joel Z. Leibo:
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. AAMAS 2023: 2827-2829 - [i59]Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. CoRR abs/2302.01180 (2023) - [i58]Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas W. Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas. CoRR abs/2305.00768 (2023) - [i57]Yiran Mao, Madeline G. Reinecke, Markus Kunesch, Edgar A. Duéñez-Guzmán, Ramona Comanescu, Julia Haas, Joel Z. Leibo:
Doing the right thing for the right reason: Evaluating artificial moral cognition by probing cost insensitivity. CoRR abs/2305.18269 (2023) - [i56]Aliya Amirova
Framework-Based Qualitative Analysis of Free Responses of Large Language Models: Algorithmic Fidelity. CoRR abs/2309.06364 (2023) - [i55]Richard Willis, Yali Du, Joel Z. Leibo, Michael Luck:
Resolving social dilemmas with minimal reward transfer. CoRR abs/2310.12928 (2023) - [i54]Levin Brinkmann, Fabian Baumann, Jean-François Bonnefon, Maxime Derex, Thomas F. Müller, Anne-Marie Nussberger, Agnieszka Czaplicka, Alberto Acerbi, Thomas L. Griffiths, Joseph Henrich, Joel Z. Leibo, Richard McElreath, Pierre-Yves Oudeyer, Jonathan Stray, Iyad Rahwan:
Machine Culture. CoRR abs/2311.11388 (2023) - [i53]Alexander Sasha Vezhnevets, John P. Agapiou, Avia Aharon, Ron Ziv, Jayd Matyas, Edgar A. Duéñez-Guzmán
Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia. CoRR abs/2312.03664 (2023) - [i52]Yali Du, Joel Z. Leibo, Usman Islam, Richard Willis, Peter Sunehag:
A Review of Cooperation in Multi-agent Learning. CoRR abs/2312.05162 (2023) - 2022
- [j9]Kevin R. McKee
Quantifying the effects of environment and population diversity in multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. 36(1): 21 (2022) - [j8]Jee Hang Lee
Importance of prefrontal meta control in human-like reinforcement learning. Frontiers Comput. Neurosci. 16 (2022) - [j7]Anil Yaman
Meta-control of social learning strategies. PLoS Comput. Biol. 18(2) (2022) - [i51]Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas, Alexander Sasha Vezhnevets, John P. Agapiou, Kevin R. McKee, Richard Everett, Janusz Marecki, Joel Z. Leibo, Thore Graepel:
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. CoRR abs/2201.01816 (2022) - [i50]Michael Bradley Johanson, Edward Hughes, Finbarr Timbers, Joel Z. Leibo:
Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning. CoRR abs/2205.06760 (2022) - [i49]Anil Yaman, Joel Z. Leibo, Giovanni Iacca, Sang Wan Lee:
The emergence of division of labor through decentralized social sanctioning. CoRR abs/2208.05568 (2022) - [i48]John P. Agapiou, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán
Melting Pot 2.0. CoRR abs/2211.13746 (2022) - 2021
- [c28]Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes:
Modelling Cooperation in Network Games with Spatio-Temporal Complexity. AAMAS 2021: 1455-1457 - [c27]Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel:
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. ICML 2021: 6187-6199 - [i47]Michiel A. Bakker, Richard Everett, Laura Weidinger, Iason Gabriel, William S. Isaac, Joel Z. Leibo, Edward Hughes:
Modelling Cooperation in Network Games with Spatio-Temporal Complexity. CoRR abs/2102.06911 (2021) - [i46]Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett:
Quantifying environment and population diversity in multi-agent reinforcement learning. CoRR abs/2102.08370 (2021) - [i45]Kevin R. McKee, Edward Hughes, Tina O. Zhu, Martin J. Chadwick, Raphael Koster, Antonio García Castañeda, Charlie Beattie, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo:
Deep reinforcement learning models the emergent dynamics of human cooperation. CoRR abs/2103.04982 (2021) - [i44]Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leibo:
A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings. CoRR abs/2106.09012 (2021) - [i43]Anil Yaman, Nicolas Bredèche, Onur Çaylak, Joel Z. Leibo, Sang Wan Lee:
Meta-control of social learning strategies. CoRR abs/2106.10015 (2021) - [i42]Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel:
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. CoRR abs/2107.06857 (2021) - [i41]Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo:
Statistical discrimination in learning agents. CoRR abs/2110.11404 (2021) - 2020
- [j6]Karl Tuyls
Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. 34(1): 7 (2020) - [j5]Yoram Bachrach
Negotiating team formation using deep reinforcement learning. Artif. Intell. 288: 103356 (2020) - [c26]Edward Hughes, Thomas W. Anthony, Tom Eccles, Joel Z. Leibo, David Balduzzi, Yoram Bachrach:
Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games. AAMAS 2020: 538-547 - [c25]Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo:
Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning. AAMAS 2020: 869-877 - [c24]Raphael Koster, Dylan Hadfield-Menell, Gillian K. Hadfield, Joel Z. Leibo:
Silly Rules Improve the Capacity of Agents to Learn Stable Enforcement and Compliance Behaviors. AAMAS 2020: 1887-1888 - [c23]David Balduzzi, Wojciech M. Czarnecki, Tom Anthony, Ian Gemp, Edward Hughes, Joel Z. Leibo
Smooth markets: A basic mechanism for organizing gradient-based learners. ICLR 2020 - [c22]Alexander Vezhnevets, Yuhuai Wu, Maria K. Eckstein, Rémi Leblond, Joel Z. Leibo:
OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning. ICML 2020: 9733-9742 - [i40]David Balduzzi, Wojciech M. Czarnecki, Thomas W. Anthony, Ian M. Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel:
Smooth markets: A basic mechanism for organizing gradient-based learners. CoRR abs/2001.04678 (2020) - [i39]Raphael Köster, Dylan Hadfield-Menell, Gillian K. Hadfield, Joel Z. Leibo:
Silly rules improve the capacity of agents to learn stable enforcement and compliance behaviors. CoRR abs/2001.09318 (2020) - [i38]Kevin R. McKee, Ian Gemp, Brian McWilliams, Edgar A. Duéñez-Guzmán, Edward Hughes, Joel Z. Leibo:
Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning. CoRR abs/2002.02325 (2020) - [i37]Edward Hughes, Thomas W. Anthony, Tom Eccles, Joel Z. Leibo, David Balduzzi, Yoram Bachrach:
Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games. CoRR abs/2003.00799 (2020) - [i36]Raphael Köster, Kevin R. McKee, Richard Everett, Laura Weidinger, William S. Isaac, Edward Hughes, Edgar A. Duéñez-Guzmán, Thore Graepel, Matthew M. Botvinick, Joel Z. Leibo:
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences. CoRR abs/2010.09054 (2020) - [i35]Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel:
Negotiating Team Formation Using Deep Reinforcement Learning. CoRR abs/2010.10380 (2020) - [i34]Charles Beattie, Thomas Köppe, Edgar A. Duéñez-Guzmán, Joel Z. Leibo:
DeepMind Lab2D. CoRR abs/2011.07027 (2020) - [i33]Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins, Kevin R. McKee, Joel Z. Leibo, Kate Larson, Thore Graepel:
Open Problems in Cooperative AI. CoRR abs/2012.08630 (2020)
2010 – 2019
- 2019
- [j4]Ben Seymour
Toward high-performance, memory-efficient, and fast reinforcement learning - Lessons from decision neuroscience. Sci. Robotics 4(26) (2019) - [c21]Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo:
Evolving Intrinsic Motivations for Altruistic Behavior. AAMAS 2019: 683-692 - [c20]Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel:
Malthusian Reinforcement Learning. AAMAS 2019: 1099-1107 - [c19]Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo:
The Imitation Game: Learned Reciprocity in Markov games. AAMAS 2019: 1934-1936 - [c18]Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas:
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. ICML 2019: 3040-3049 - [c17]Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel:
Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. ALIFE 2019: 103-110 - [c16]Ben Deverett, Ryan Faulkner, Meire Fortunato, Gregory Wayne, Joel Z. Leibo
Interval timing in deep reinforcement learning agents. NeurIPS 2019: 6686-6695 - [c15]Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià Puigdomènech Badia, Gavin Buttimore, Charlie Deck, Joel Z. Leibo, Charles Blundell:
Generalization of Reinforcement Learners with Working and Episodic Memory. NeurIPS 2019: 12448-12457 - [i32]Joel Z. Leibo, Edward Hughes, Marc Lanctot, Thore Graepel:
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research. CoRR abs/1903.00742 (2019) - [i31]Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo:
Learning Reciprocity in Complex Sequential Social Dilemmas. CoRR abs/1903.08082 (2019) - [i30]Ben Deverett, Ryan Faulkner, Meire Fortunato, Greg Wayne, Joel Z. Leibo:
Interval timing in deep reinforcement learning agents. CoRR abs/1905.13469 (2019) - [i29]Alexander Sasha Vezhnevets, Yuhuai Wu, Rémi Leblond, Joel Z. Leibo:
Options as responses: Grounding behavioural hierarchies in multi-agent RL. CoRR abs/1906.01470 (2019) - [i28]Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià Puigdomènech Badia, Gavin Buttimore, Charlie Deck, Joel Z. Leibo, Charles Blundell:
Generalization of Reinforcement Learners with Working and Episodic Memory. CoRR abs/1910.13406 (2019) - 2018
- [c14]Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys:
Deep Q-learning From Demonstrations. AAAI 2018: 3223-3230 - [c13]Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel:
A Generalised Method for Empirical Game Theoretic Analysis. AAMAS 2018: 77-85 - [c12]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. AAMAS 2018: 2085-2087 - [c11]Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark:
Emergent Communication through Negotiation. ICLR (Poster) 2018 - [c10]Edward Hughes, Joel Z. Leibo, Matthew Phillips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel:
Inequity aversion improves cooperation in intertemporal social dilemmas. NeurIPS 2018: 3330-3340 - [i27]Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran, David Amos, Charles Beattie, Keith Anderson, Antonio García Castañeda, Manuel Sanchez, Simon Green, Audrunas Gruslys, Shane Legg, Demis Hassabis, Matthew M. Botvinick:
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. CoRR abs/1801.08116 (2018) - [i26]Simon Schmitt, Jonathan J. Hudson, Augustin Zídek, Simon Osindero, Carl Doersch, Wojciech M. Czarnecki, Joel Z. Leibo, Heinrich Küttler, Andrew Zisserman, Karen Simonyan, S. M. Ali Eslami:
Kickstarting Deep Reinforcement Learning. CoRR abs/1803.03835 (2018) - [i25]Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel:
A Generalised Method for Empirical Game Theoretic Analysis. CoRR abs/1803.06376 (2018) - [i24]Edward Hughes, Joel Z. Leibo, Matthew G. Philips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel:
Inequity aversion resolves intertemporal social dilemmas. CoRR abs/1803.08884 (2018) - [i23]Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack W. Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Jimenez Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matthew M. Botvinick, Demis Hassabis, Timothy P. Lillicrap:
Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR abs/1803.10760 (2018) - [i22]Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark:
Emergent Communication through Negotiation. CoRR abs/1804.03980 (2018) - [i21]Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel:
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. CoRR abs/1807.01281 (2018) - [i20]Natasha Jaques
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR abs/1810.08647 (2018) - [i19]Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo:
Evolving intrinsic motivations for altruistic behavior. CoRR abs/1811.05931 (2018) - [i18]Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel:
Malthusian Reinforcement Learning. CoRR abs/1812.07019 (2018) - 2017
- [c9]Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel:
Multi-agent Reinforcement Learning in Sequential Social Dilemmas. AAMAS 2017: 464-473 - [c8]Jane Wang, Zeb Kurth-Nelson, Hubert Soyer, Joel Z. Leibo, Dhruva Tirumala, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matt M. Botvinick:
Learning to reinforcement learn. CogSci 2017 - [c7]Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo
Reinforcement Learning with Unsupervised Auxiliary Tasks. ICLR 2017 - [c6]Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel:
A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS 2017: 3643-3652 - [i17]Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel:
Multi-agent Reinforcement Learning in Sequential Social Dilemmas. CoRR abs/1702.03037 (2017) - [i16]Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys:
Learning from Demonstrations for Real World Reinforcement Learning. CoRR abs/1704.03732 (2017) - [i15]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning. CoRR abs/1706.05296 (2017) - [i14]Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel:
A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR abs/1707.06600 (2017) - [i13]Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani
Symmetric Decomposition of Asymmetric Games. CoRR abs/1711.05074 (2017) - [i12]Matthew M. Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis:
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR abs/1711.08378 (2017) - 2016
- [j3]Fabio Anselmi
Unsupervised learning of invariant representations. Theor. Comput. Sci. 633: 112-121 (2016) - [c5]Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio:
How Important Is Weight Symmetry in Backpropagation? AAAI 2016: 1837-1844 - [c4]Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu:
Using Fast Weights to Attend to the Recent Past. NIPS 2016: 4331-4339 - [i11]Joel Z. Leibo, Qianli Liao, Winrich Freiwald, Fabio Anselmi, Tomaso A. Poggio:
View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation. CoRR abs/1606.01552 (2016) - [i10]Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z. Leibo, Jack W. Rae, Daan Wierstra, Demis Hassabis:
Model-Free Episodic Control. CoRR abs/1606.04460 (2016) - [i9]Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu:
Using Fast Weights to Attend to the Recent Past. CoRR abs/1610.06258 (2016) - [i8]Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu:
Reinforcement Learning with Unsupervised Auxiliary Tasks. CoRR abs/1611.05397 (2016) - [i7]Jane X. Wang, Zeb Kurth-Nelson, Dhruva Tirumala, Hubert Soyer, Joel Z. Leibo, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matthew M. Botvinick:
Learning to reinforcement learn. CoRR abs/1611.05763 (2016) - [i6]Charles Beattie, Joel Z. Leibo, Denis Teplyashin, Tom Ward, Marcus Wainwright, Heinrich Küttler, Andrew Lefrancq, Simon Green, Víctor Valdés, Amir Sadik, Julian Schrittwieser, Keith Anderson, Sarah York, Max Cant, Adam Cain, Adrian Bolton, Stephen Gaffney, Helen King, Demis Hassabis, Shane Legg, Stig Petersen:
DeepMind Lab. CoRR abs/1612.03801 (2016) - 2015
- [j2]Joel Z. Leibo, Qianli Liao, Fabio Anselmi
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. PLoS Comput. Biol. 11(10) (2015) - [i5]Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio:
How Important is Weight Symmetry in Backpropagation? CoRR abs/1510.05067 (2015) - [i4]Joel Z. Leibo, Julien Cornebise, Sergio Gómez, Demis Hassabis:
Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation. CoRR abs/1512.08457 (2015) - 2014
- [c3]Joel Z. Leibo, Qianli Liao, Tomaso A. Poggio:
Subtasks of Unconstrained Face Recognition. VISAPP (2) 2014: 113-121 - [i3]Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio:
Unsupervised learning of clutter-resistant visual representations from natural videos. CoRR abs/1409.3879 (2014) - 2013
- [c2]Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio:
Learning invariant representations and applications to face verification. NIPS 2013: 3057-3065 - [p1]Cheston Tan
Throwing Down the Visual Intelligence Gauntlet. Machine Learning for Computer Vision 2013: 1-15 - [i2]Qianli Liao, Joel Z. Leibo, Youssef Mroueh, Tomaso A. Poggio:
Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines? CoRR abs/1311.4082 (2013) - [i1]Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio:
Unsupervised Learning of Invariant Representations in Hierarchical Architectures. CoRR abs/1311.4158 (2013) - 2012
- [j1]Leyla Isik, Joel Z. Leibo
Learning and disrupting invariance in visual recognition with a temporal association rule. Frontiers Comput. Neurosci. 6: 37 (2012) - 2011
- [c1]Joel Z. Leibo, Jim Mutch, Tomaso A. Poggio:
Why The Brain Separates Face Recognition From Object Recognition. NIPS 2011: 711-719
Coauthor Index
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last updated on 2024-12-10 21:43 CET by the dblp team
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