Timezone: »
Poster
The rat as particle filter
Nathaniel D Daw · Aaron Courville
Author Information
Nathaniel D Daw (New York University)
Nathaniel Daw is Assistant Professor of Neural Science and Psychology and Affiliated Assistant Professor of Computer Science at New York University. Prior to this he completed his PhD in Computer Science at Carnegie Mellon University and pursued postdoctoral research at the Gatsby Computational Neuroscience Unit at UCL. His research concerns reinforcement learning and decision making from a computational approach, and particularly the application of computational models to the analysis of behavioral and neural data. He is the recipient of a McKnight Scholar Award, a NARSAD Young Investigator Award, and a Royal Society USA Research Fellowship.
Aaron Courville (Mila, U. Montreal)
Related Events (a corresponding poster, oral, or spotlight)
-
2007 Spotlight: The rat as particle filter »
Thu. Dec 6th 01:20 -- 01:30 AM Room
More from the Same Authors
-
2021 Spotlight: A Variational Perspective on Diffusion-Based Generative Models and Score Matching »
Chin-Wei Huang · Jae Hyun Lim · Aaron Courville -
2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization »
Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine -
2021 : Behavior Predictive Representations for Generalization in Reinforcement Learning »
Siddhant Agarwal · Aaron Courville · Rishabh Agarwal -
2021 : MIDI-DDSP: Hierarchical Modeling of Music for Detailed Control »
Yusong Wu · Ethan Manilow · Kyle Kastner · Tim Cooijmans · Aaron Courville · Cheng-Zhi Anna Huang · Jesse Engel -
2022 : Datasets That Are Not: Evolving Novelty Through Sparsity and Iterated Learning »
Yusong Wu · Kyle Kastner · Tim Cooijmans · Cheng-Zhi Anna Huang · Aaron Courville -
2022 : Unleashing The Potential of Data Sharing in Ensemble Deep Reinforcement Learning »
Zhixuan Lin · Pierluca D'Oro · Evgenii Nikishin · Aaron Courville -
2022 : Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier »
Pierluca D'Oro · Max Schwarzer · Evgenii Nikishin · Pierre-Luc Bacon · Marc Bellemare · Aaron Courville -
2022 : Investigating Multi-task Pretraining and Generalization in Reinforcement Learning »
Adrien Ali Taiga · Rishabh Agarwal · Jesse Farebrother · Aaron Courville · Marc Bellemare -
2023 : Learning Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy »
Max Schwarzer · Jesse Farebrother · Joshua Greaves · Kevin Roccapriore · Ekin Dogus Cubuk · Rishabh Agarwal · Aaron Courville · Marc Bellemare · Sergei Kalinin · Igor Mordatch · Pablo Samuel Castro -
2023 Poster: Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets »
Dinghuai Zhang · Hanjun Dai · Nikolay Malkin · Aaron Courville · Yoshua Bengio · Ling Pan -
2023 Poster: Versatile Energy-Based Probabilistic Models for High Energy Physics »
Taoli Cheng · Aaron Courville -
2023 Poster: Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings »
Yi Ren · Samuel Lavoie · Michael Galkin · Danica J. Sutherland · Aaron Courville -
2023 Poster: Double Gumbel Q-Learning »
David Yu-Tung Hui · Aaron Courville · Pierre-Luc Bacon -
2023 Poster: Group Robust Classification Without Any Group Information »
Christos Tsirigotis · Joao Monteiro · Pau Rodriguez · David Vazquez · Aaron Courville -
2023 Poster: Language Model Alignment with Elastic Reset »
Michael Noukhovitch · Samuel Lavoie · Florian Strub · Aaron Courville -
2022 Poster: Riemannian Diffusion Models »
Chin-Wei Huang · Milad Aghajohari · Joey Bose · Prakash Panangaden · Aaron Courville -
2022 Poster: Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress »
Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare -
2021 : Behavior Predictive Representations for Generalization in Reinforcement Learning »
Siddhant Agarwal · Aaron Courville · Rishabh Agarwal -
2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization Q&A »
Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine -
2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization »
Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine -
2021 Poster: Gradient Starvation: A Learning Proclivity in Neural Networks »
Mohammad Pezeshki · Oumar Kaba · Yoshua Bengio · Aaron Courville · Doina Precup · Guillaume Lajoie -
2021 Poster: Pretraining Representations for Data-Efficient Reinforcement Learning »
Max Schwarzer · Nitarshan Rajkumar · Michael Noukhovitch · Ankesh Anand · Laurent Charlin · R Devon Hjelm · Philip Bachman · Aaron Courville -
2021 Poster: A Variational Perspective on Diffusion-Based Generative Models and Score Matching »
Chin-Wei Huang · Jae Hyun Lim · Aaron Courville -
2021 Oral: Deep Reinforcement Learning at the Edge of the Statistical Precipice »
Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare -
2021 Poster: Deep Reinforcement Learning at the Edge of the Statistical Precipice »
Rishabh Agarwal · Max Schwarzer · Pablo Samuel Castro · Aaron Courville · Marc Bellemare -
2020 Workshop: AI for Earth Sciences »
Surya Karthik Mukkavilli · Johanna Hansen · Natasha Dudek · Tom Beucler · Kelly Kochanski · Mayur Mudigonda · Karthik Kashinath · Amy McGovern · Paul D Miller · Chad Frischmann · Pierre Gentine · Gregory Dudek · Aaron Courville · Daniel Kammen · Vipin Kumar -
2020 Poster: Unsupervised Learning of Dense Visual Representations »
Pedro O. Pinheiro · Amjad Almahairi · Ryan Benmalek · Florian Golemo · Aaron Courville -
2019 Poster: Ordered Memory »
Yikang Shen · Shawn Tan · Arian Hosseini · Zhouhan Lin · Alessandro Sordoni · Aaron Courville -
2019 Poster: MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis »
Kundan Kumar · Rithesh Kumar · Thibault de Boissiere · Lucas Gestin · Wei Zhen Teoh · Jose Sotelo · Alexandre de Brébisson · Yoshua Bengio · Aaron Courville -
2019 Poster: No-Press Diplomacy: Modeling Multi-Agent Gameplay »
Philip Paquette · Yuchen Lu · SETON STEVEN BOCCO · Max Smith · Satya O.-G. · Jonathan K. Kummerfeld · Joelle Pineau · Satinder Singh · Aaron Courville -
2018 Workshop: Visually grounded interaction and language »
Florian Strub · Harm de Vries · Erik Wijmans · Samyak Datta · Ethan Perez · Mateusz Malinowski · Stefan Lee · Peter Anderson · Aaron Courville · Jeremie MARY · Dhruv Batra · Devi Parikh · Olivier Pietquin · Chiori HORI · Tim Marks · Anoop Cherian -
2018 Poster: Improving Explorability in Variational Inference with Annealed Variational Objectives »
Chin-Wei Huang · Shawn Tan · Alexandre Lacoste · Aaron Courville -
2018 Poster: Towards Text Generation with Adversarially Learned Neural Outlines »
Sandeep Subramanian · Sai Rajeswar Mudumba · Alessandro Sordoni · Adam Trischler · Aaron Courville · Chris Pal -
2017 Workshop: Visually grounded interaction and language »
Florian Strub · Harm de Vries · Abhishek Das · Satwik Kottur · Stefan Lee · Mateusz Malinowski · Olivier Pietquin · Devi Parikh · Dhruv Batra · Aaron Courville · Jeremie Mary -
2017 Poster: Improved Training of Wasserstein GANs »
Ishaan Gulrajani · Faruk Ahmed · Martin Arjovsky · Vincent Dumoulin · Aaron Courville -
2017 Poster: GibbsNet: Iterative Adversarial Inference for Deep Graphical Models »
Alex Lamb · R Devon Hjelm · Yaroslav Ganin · Joseph Paul Cohen · Aaron Courville · Yoshua Bengio -
2017 Poster: Modulating early visual processing by language »
Harm de Vries · Florian Strub · Jeremie Mary · Hugo Larochelle · Olivier Pietquin · Aaron Courville -
2017 Spotlight: Modulating early visual processing by language »
Harm de Vries · Florian Strub · Jeremie Mary · Hugo Larochelle · Olivier Pietquin · Aaron Courville -
2016 : Discussion panel »
Ian Goodfellow · Soumith Chintala · Arthur Gretton · Sebastian Nowozin · Aaron Courville · Yann LeCun · Emily Denton -
2016 : Adversarially Learned Inference (ALI) and BiGANs »
Aaron Courville -
2016 Poster: Professor Forcing: A New Algorithm for Training Recurrent Networks »
Alex M Lamb · Anirudh Goyal · Ying Zhang · Saizheng Zhang · Aaron Courville · Yoshua Bengio -
2015 : Introduction »
Aaron Courville -
2015 Workshop: Multimodal Machine Learning »
Louis-Philippe Morency · Tadas Baltrusaitis · Aaron Courville · Kyunghyun Cho -
2015 Poster: A Recurrent Latent Variable Model for Sequential Data »
Junyoung Chung · Kyle Kastner · Laurent Dinh · Kratarth Goel · Aaron Courville · Yoshua Bengio -
2014 Poster: Generative Adversarial Nets »
Ian Goodfellow · Jean Pouget-Abadie · Mehdi Mirza · Bing Xu · David Warde-Farley · Sherjil Ozair · Aaron Courville · Yoshua Bengio -
2013 Poster: Multi-Prediction Deep Boltzmann Machines »
Ian Goodfellow · Mehdi Mirza · Aaron Courville · Yoshua Bengio -
2011 Poster: Environmental statistics and the trade-off between model-based and TD learning in humans »
Dylan A Simon · Nathaniel D Daw -
2011 Poster: On Tracking The Partition Function »
Guillaume Desjardins · Aaron Courville · Yoshua Bengio -
2010 Tutorial: Reinforcement Learning in Humans and Other Animals »
Nathaniel D Daw -
2009 Poster: An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism »
Aaron Courville · Douglas Eck · Yoshua Bengio -
2009 Session: Oral Session 3: Deep Learning and Network Models »
Aaron Courville -
2008 Workshop: Machine learning meets human learning »
Nathaniel D Daw · Tom Griffiths · Josh Tenenbaum · Jerry Zhu -
2008 Session: Oral session 11: Attention and Mind »
Aaron Courville