Lars Buesing

According to our database, Lars Buesing authored at least 40 papers between 2007 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations.

Matko Bosnjak, Pierre Harvey Richemond, Nenad Tomasev, Florian Strub, Jacob C. Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?

Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

CoRR, 2022

Making Sense of Raw Input (Extended Abstract).

Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek J. Sergot

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Advancing mathematics by guiding human intuition with AI.

Alex Davies, Petar Velickovic, Lars Buesing, Sam Blackwell, Daniel Zheng, Nenad Tomasev, Richard Tanburn, Peter W. Battaglia, Charles Blundell, András Juhász, Marc Lackenby, Geordie Williamson, Demis Hassabis, Pushmeet Kohli

Nat., 2021

Making sense of raw input.

Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David P. Reichert, Pushmeet Kohli, Marek J. Sergot

Artif. Intell., 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, Rémi Munos

Proceedings of the 38th International Conference on Machine Learning, 2021

Representation Learning via Invariant Causal Mechanisms.

Jovana Mitrovic, Brian McWilliams, Jacob C. Walker, Lars Holger Buesing, Charles Blundell

Proceedings of the 9th International Conference on Learning Representations, 2021

On the role of planning in model-based deep reinforcement learning.

Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.

Thomas Mesnard, Théophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Tom Stepleton, Nicolas Heess, Arthur Guez, Marcus Hutter, Lars Buesing, Rémi Munos

CoRR, 2020

Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban.

Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber

CoRR, 2020

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning.

Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt, Arthur Guez, Saran Tunyasuvunakool, Alistair Muldal, Théophane Weber, Péter Karkus, Sébastien Racanière, Lars Buesing, Timothy P. Lillicrap, Nicolas Heess

CoRR, 2020

Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning.

Giambattista Parascandolo, Lars Buesing, Josh Merel, Leonard Hasenclever, John Aslanides, Jessica B. Hamrick, Nicolas Heess, Alexander Neitz, Theophane Weber

CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.

Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing

CoRR, 2020

Pointer Graph Networks.

Petar Velickovic, Lars Buesing, Matthew C. Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Value-driven Hindsight Modelling.

Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Proceedings of the 8th International Conference on Learning Representations, 2020

Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions.

Lars Buesing, Nicolas Heess, Theophane Weber

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Temporal Difference Variational Auto-Encoder.

Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber

Proceedings of the 7th International Conference on Learning Representations, 2019

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search.

Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau

Proceedings of the 7th International Conference on Learning Representations, 2019

Credit Assignment Techniques in Stochastic Computation Graphs.

Théophane Weber, Nicolas Heess, Lars Buesing, David Silver

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning and Querying Fast Generative Models for Reinforcement Learning.

Lars Buesing, Theophane Weber, Sébastien Racanière, S. M. Ali Eslami, Danilo Jimenez Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra

CoRR, 2018

2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

Theophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, David Silver, Daan Wierstra

CoRR, 2017

Learning model-based planning from scratch.

Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sébastien Racanière, David P. Reichert, Theophane Weber, Daan Wierstra, Peter W. Battaglia

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

Sébastien Racanière, Theophane Weber, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, Demis Hassabis, David Silver, Daan Wierstra

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2015

Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM).

Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó, Lars Buesing, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

High-dimensional neural spike train analysis with generalized count linear dynamical systems.

Yuanjun Gao, Lars Buesing, Krishna V. Shenoy, John P. Cunningham

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Clustered factor analysis of multineuronal spike data.

Lars Buesing, Timothy A. Machado, John P. Cunningham, Liam Paninski

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity.

Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass

PLoS Comput. Biol., 2013

Inferring neural population dynamics from multiple partial recordings of the same neural circuit.

Srinivas C. Turaga, Lars Buesing, Adam M. Packer, Henry Dalgleish, Noah Pettit, Michael Häusser, Jakob H. Macke

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Spectral learning of linear dynamics from generalised-linear observations with application to neural population data.

Lars Buesing, Jakob H. Macke, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons.

Dejan Pecevski, Lars Buesing, Wolfgang Maass

PLoS Comput. Biol., 2011

Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons.

Lars Buesing, Johannes Bill, Bernhard Nessler, Wolfgang Maass

PLoS Comput. Biol., 2011

Empirical models of spiking in neural populations.

Jakob H. Macke, Lars Buesing, John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons.

Lars Büsing, Benjamin Schrauwen, Robert Legenstein

Neural Comput., 2010

A Spiking Neuron as Information Bottleneck.

Lars Buesing, Wolfgang Maass

Neural Comput., 2010

2008

Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression.

Claudia Clopath, Lorric Ziegler, Eleni Vasilaki, Lars Büsing, Wulfram Gerstner

PLoS Comput. Biol., 2008

On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing.

Benjamin Schrauwen, Lars Buesing, Robert Legenstein

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories.

Eilif Mueller, Lars Buesing, Johannes Schemmel, Karlheinz Meier

Neural Comput., 2007

Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons.

Lars Buesing, Wolfgang Maass

Proceedings of the Advances in Neural Information Processing Systems 20, 2007