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Author Information
Grace Lindsay (University College London)
George Konidaris (Brown University)
Shakir Mohamed (DeepMind)

Shakir Mohamed is a senior staff scientist at DeepMind in London. Shakir's main interests lie at the intersection of approximate Bayesian inference, deep learning and reinforcement learning, and the role that machine learning systems at this intersection have in the development of more intelligent and general-purpose learning systems. Before moving to London, Shakir held a Junior Research Fellowship from the Canadian Institute for Advanced Research (CIFAR), based in Vancouver at the University of British Columbia with Nando de Freitas. Shakir completed his PhD with Zoubin Ghahramani at the University of Cambridge, where he was a Commonwealth Scholar to the United Kingdom. Shakir is from South Africa and completed his previous degrees in Electrical and Information Engineering at the University of the Witwatersrand, Johannesburg.
Kimberly Stachenfeld (DeepMind)
Peter Dayan (Max Planck Institute for Biological Cybernetics)
Yael Niv (Princeton University)
Yael Niv received her MA in psychobiology from Tel Aviv University and her PhD from the Hebrew University in Jerusalem, having conducted a major part of her thesis research at the Gatsby Computational Neuroscience Unit in UCL. After a short postdoc at Princeton she became faculty at the Psychology Department and the Princeton Neuroscience Institute. Her lab's research focuses on the neural and computational processes underlying reinforcement learning and decision-making in humans and animals, with a particular focus on representation learning. She recently co-founded the Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry, and is currently taking the research in her lab in the direction of computational psychiatry.
Doina Precup (McGill University / Mila / DeepMind Montreal)
Catherine Hartley (New York University)
Ishita Dasgupta (Harvard University)
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2022 : Invited talk: "Predicting mouse neural activity with models trained through supervised, unsupervised, and reinforcement learning" »
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2022 Spotlight: Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex »
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2022 Workshop: 3rd Offline Reinforcement Learning Workshop: Offline RL as a "Launchpad" »
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2022 Poster: Model-based Lifelong Reinforcement Learning with Bayesian Exploration »
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2021 Workshop: Offline Reinforcement Learning »
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2021 : George Konidaris Talk Q&A »
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2021 Oral: Passive attention in artificial neural networks predicts human visual selectivity »
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2020 : Closing remarks »
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2020 : Invited Talk #7 QnA - Yael Niv »
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2020 : Invited Talk #7 Yael Niv - Latent causes, prediction errors and the organization of memory »
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2020 : Speaker Introduction: Yael Niv »
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2020 : Invited Talk #6 QnA - Catherine Hartley »
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2020 : Invited Talk #5 Ishita Dasgupta - Embedding structure in data: Progress and challenges for the meta-learning approach »
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2020 : Invited Talk #3 QnA - Kim Stachenfeld »
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2020 : Invited Talk #3 Kim Stachenfeld : Structure Learning and the Hippocampal-Entorhinal Circuit »
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2020 : Contributed Talk #1: Learning multi-dimensional rules with probabilistic feedback via value-based serial hypothesis testing »
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2020 : Invited talk 1 QnA: Shakir Mohamed »
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2020 : Organizers Opening Remarks »
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2020 : Keynote: Doina Precup »
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2020 : Q&A with Shakir »
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2020 : Invited: Shakir Mohamed »
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2020 Poster: Reward Propagation Using Graph Convolutional Networks »
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2020 : Policy Panel »
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2020 Poster: An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay »
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2020 Poster: Forethought and Hindsight in Credit Assignment »
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2020 Affinity Workshop: Muslims in ML »
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2019 : Panel Session: A new hope for neuroscience »
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2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Poster Spotlight 2 »
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2019 : Panel Discussion »
Richard Sutton · Doina Precup -
2019 : Poster and Coffee Break 1 »
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2019 : Invited Talk: Hierarchical Reinforcement Learning: Computational Advances and Neuroscience Connections »
Doina Precup -
2019 : Panel Discussion led by Grace Lindsay »
Grace Lindsay · Blake Richards · Doina Precup · Jacqueline Gottlieb · Jeff Clune · Jane Wang · Richard Sutton · Angela Yu · Ida Momennejad -
2019 : Coffee/Poster session 2 »
Xingyou Song · Puneet Mangla · David Salinas · Zhenxun Zhuang · Leo Feng · Shell Xu Hu · Raul Puri · Wesley Maddox · Aniruddh Raghu · Prudencio Tossou · Mingzhang Yin · Ishita Dasgupta · Kangwook Lee · Ferran Alet · Zhen Xu · Jörg Franke · James Harrison · Jonathan Warrell · Guneet Dhillon · Arber Zela · Xin Qiu · Julien Niklas Siems · Russell Mendonca · Louis Schlessinger · Jeffrey Li · Georgiana Manolache · Debojyoti Dutta · Lucas Glass · Abhishek Singh · Gregor Koehler -
2019 : Opening Remarks »
Raymond Chua · Feryal Behbahani · Sara Zannone · Rui Ponte Costa · Claudia Clopath · Doina Precup · Blake Richards -
2019 Workshop: Biological and Artificial Reinforcement Learning »
Raymond Chua · Sara Zannone · Feryal Behbahani · Rui Ponte Costa · Claudia Clopath · Blake Richards · Doina Precup -
2019 Poster: Training Language GANs from Scratch »
Cyprien de Masson d'Autume · Shakir Mohamed · Mihaela Rosca · Jack Rae -
2019 Poster: Disentangled behavioural representations »
Amir Dezfouli · Hassan Ashtiani · Omar Ghattas · Richard Nock · Peter Dayan · Cheng Soon Ong -
2019 Poster: Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks »
Sitao Luan · Mingde Zhao · Xiao-Wen Chang · Doina Precup -
2018 Poster: Implicit Reparameterization Gradients »
Mikhail Figurnov · Shakir Mohamed · Andriy Mnih -
2018 Spotlight: Implicit Reparameterization Gradients »
Mikhail Figurnov · Shakir Mohamed · Andriy Mnih -
2018 Poster: Temporal Regularization for Markov Decision Process »
Pierre Thodoroff · Audrey Durand · Joelle Pineau · Doina Precup -
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Jessie Huang · Fa Wu · Doina Precup · Yang Cai -
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2017 : Progress on Deep Reinforcement Learning with Temporal Abstraction (Doina Precup) »
Doina Precup -
2017 : Doina Precup »
Doina Precup -
2017 Workshop: Hierarchical Reinforcement Learning »
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Yael Niv -
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2017 Poster: Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes »
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2017 Oral: Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes »
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2016 : Panel Discussion »
Shakir Mohamed · David Blei · Ryan Adams · José Miguel Hernández-Lobato · Ian Goodfellow · Yarin Gal -
2016 : Bayesian Agents: Bayesian Reasoning and Deep Learning in Agent-based Systems »
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2016 Workshop: The Future of Interactive Machine Learning »
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2016 Tutorial: Variational Inference: Foundations and Modern Methods »
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2015 Workshop: Advances in Approximate Bayesian Inference »
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2015 Poster: Data Generation as Sequential Decision Making »
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2014 Workshop: Advances in Variational Inference »
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Odalric-Ambrym Maillard · Timothy A Mann · Shie Mannor · Jeremie Mary · Laurent Orseau · Thomas Dietterich · Ronald Ortner · Peter Grünwald · Joelle Pineau · Raphael Fonteneau · Georgios Theocharous · Esteban D Arcaute · Christos Dimitrakakis · Nan Jiang · Doina Precup · Pierre-Luc Bacon · Marek Petrik · Aviv Tamar -
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2014 Spotlight: Optimizing Energy Production Using Policy Search and Predictive State Representations »
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2014 Poster: Semi-supervised Learning with Deep Generative Models »
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2014 Spotlight: Semi-supervised Learning with Deep Generative Models »
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2013 Poster: Learning from Limited Demonstrations »
Beomjoon Kim · Amir-massoud Farahmand · Joelle Pineau · Doina Precup -
2013 Poster: Bellman Error Based Feature Generation using Random Projections on Sparse Spaces »
Mahdi Milani Fard · Yuri Grinberg · Amir-massoud Farahmand · Joelle Pineau · Doina Precup -
2013 Spotlight: Learning from Limited Demonstrations »
Beomjoon Kim · Amir-massoud Farahmand · Joelle Pineau · Doina Precup -
2012 Workshop: Bayesian Optimization and Decision Making »
Javad Azimi · Roman Garnett · Frank R Hutter · Shakir Mohamed -
2012 Poster: Value Pursuit Iteration »
Amir-massoud Farahmand · Doina Precup -
2012 Poster: Expectation Propagation in Gaussian Process Dynamical Systems »
Marc Deisenroth · Shakir Mohamed -
2012 Poster: On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization »
Andre S Barreto · Doina Precup · Joelle Pineau -
2012 Poster: Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression »
Mohammad Emtiyaz Khan · Shakir Mohamed · Kevin Murphy -
2011 Poster: TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning »
George Konidaris · Scott Niekum · Philip Thomas -
2011 Poster: Reinforcement Learning using Kernel-Based Stochastic Factorization »
Andre S Barreto · Doina Precup · Joelle Pineau -
2010 Poster: Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories »
George Konidaris · Scott R Kuindersma · Andrew G Barto · Roderic A Grupen -
2009 Poster: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining »
George Konidaris · Andrew G Barto -
2009 Spotlight: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining »
George Konidaris · Andrew G Barto -
2009 Poster: Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process »
Shakir Mohamed · David A Knowles · Zoubin Ghahramani · Finale P Doshi-Velez -
2009 Poster: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2009 Spotlight: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2008 Poster: Bayesian Exponential Family PCA »
Shakir Mohamed · Katherine Heller · Zoubin Ghahramani -
2008 Spotlight: Bayesian Exponential Family PCA »
Shakir Mohamed · Katherine Heller · Zoubin Ghahramani -
2008 Poster: Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement »
Michael Todd · Yael Niv · Jonathan D Cohen -
2008 Oral: Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement »
Michael Todd · Yael Niv · Jonathan D Cohen -
2008 Poster: Bounding Performance Loss in Approximate MDP Homomorphisms »
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2007 Workshop: Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 2) »
Yael Niv · Matthew Botvinick · Andrew G Barto -
2007 Workshop: Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 1) »
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