Buesing, Lars

18 publications

IJCAI 2022 Making Sense of Raw Input (Extended Abstract) Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek J. Sergot

ICML 2021 Counterfactual Credit Assignment in Model-Free Reinforcement Learning Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos

AISTATS 2020 Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions Lars Buesing, Nicolas Heess, Theophane Weber

ICLR 2020 Combining Q-Learning and Search with Amortized Value Estimates Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Theophane Weber, Lars Buesing, Peter W. Battaglia

NeurIPS 2020 Pointer Graph Networks Petar Veličković, Lars Buesing, Matthew Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell

NeurIPS 2020 Value-Driven Hindsight Modelling Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess

AISTATS 2019 Credit Assignment Techniques in Stochastic Computation Graphs Théophane Weber, Nicolas Heess, Lars Buesing, David Silver

ICLR 2019 Temporal Difference Variational Auto-Encoder Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber

ICLR 2019 Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sebastien Racaniere, Arthur Guez, Jean-Baptiste Lespiau

NeurIPS 2017 Fast Amortized Inference of Neural Activity from Calcium Imaging Data with Variational Autoencoders Artur Speiser, Jinyao Yan, Evan W Archer, Lars Buesing, Srinivas C. Turaga, Jakob H Macke

NeurIPS 2017 Imagination-Augmented Agents for Deep Reinforcement Learning Sébastien Racanière, Theophane Weber, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra

NeurIPS 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltan Szabo, Lars Buesing, Maneesh Sahani

NeurIPS 2014 Clustered Factor Analysis of Multineuronal Spike Data Lars Buesing, Timothy A Machado, John P. Cunningham, Liam Paninski

NeurIPS 2013 Inferring Neural Population Dynamics from Multiple Partial Recordings of the Same Neural Circuit Srini Turaga, Lars Buesing, Adam M Packer, Henry Dalgleish, Noah Pettit, Michael Hausser, Jakob H Macke

NeurIPS 2012 Spectral Learning of Linear Dynamics from Generalised-Linear Observations with Application to Neural Population Data Lars Buesing, Jakob H. Macke, Maneesh Sahani

NeurIPS 2011 Empirical Models of Spiking in Neural Populations Jakob H. Macke, Lars Buesing, John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

NeurIPS 2008 On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing Benjamin Schrauwen, Lars Buesing, Robert A. Legenstein

NeurIPS 2007 Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons Lars Buesing, Wolfgang Maass