Lars Buesing

发表

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

Wolfgang Maass, Lars Buesing, Lars Buesing, 2007, NIPS.

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

Wittawat Jitkrittum, Zoltán Szabó, Maneesh Sahani, 2015, NIPS.

Learning stable, regularised latent models of neural population dynamics

Maneesh Sahani, Lars Buesing, Jakob H Macke, 2012, Network.

Learning Dynamic State Abstractions for Model-Based Reinforcement Learning

Demis Hassabis, Karol Gregor, Fabio Viola, 2018 .

Imagination-Augmented Agents for Deep Reinforcement Learning

Razvan Pascanu, Demis Hassabis, David Silver, 2017, NIPS.

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

Maneesh Sahani, Jakob H. Macke, Lars Buesing, 2012, NIPS.

Stitching neural activity in space and time: theory and practice

Jakob H. Macke, Srinivas C. Turaga, Lars Buesing, 2016 .

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Stefan Habenschuss, Wolfgang Maass, Lars Buesing, 2015, PloS one.

Robust estimation for neural state-space models

Jakob H. Macke, Lars Buesing, M Sahani, 2013 .

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

Benjamin Schrauwen, Robert A. Legenstein, Lars Buesing, 2010, Neural Computation.

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

Wolfgang Maass, Lars Buesing, Johannes Bill, 2011, PLoS Comput. Biol..

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

Wolfgang Maass, Lars Buesing, Dejan Pecevski, 2011, PLoS Comput. Biol..

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

Nicolas Heess, Lars Buesing, Arthur Guez, 2018, ICLR.

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

Nicolas Heess, Lars Buesing, Theophane Weber, 2019, AISTATS.

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

John P. Cunningham, Krishna V. Shenoy, Lars Buesing, 2015, NIPS.

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning pdf

Andrew Jaegle, Jonathan J. Hunt, Nicolas Heess, 2020, ArXiv.

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

Jessica B. Hamrick, John Aslanides, Leonard Hasenclever, 2020, ArXiv.

Causally Correct Partial Models for Reinforcement Learning pdf

Fabio Viola, Karol Gregor, Lars Buesing, 2020, ArXiv.

Credit Assignment Techniques in Stochastic Computation Graphs

David Silver, Nicolas Heess, Lars Buesing, 2019, AISTATS.

Local inhibition facilitates synaptic learning in spatially extended Bayesian spiking networks

Stefan Habenschuss, Wolfgang Maass, Lars Buesing, 2013 .

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

Mijung Park, Wittawat Jitkrittum, Maneesh Sahani, 2014 .

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

Jessica B. Hamrick, Fabio Viola, Petar Velickovic, 2020, ArXiv.

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

Johannes Schemmel, Karlheinz Meier, Eilif Müller, 2007, Neural Computation.

Empirical models of spiking in neural populations

John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, 2011, NIPS.

Pointer Graph Networks pdf

Razvan Pascanu, Charles Blundell, Lars Buesing, 2020, NeurIPS.

A hierarchy of recurrent networks for speech recognition

Benjamin Schrauwen, Lars Buesing, Lars Buesing, 2009, NIPS 2009.

Representation Learning via Invariant Causal Mechanisms pdf

Charles Blundell, Lars Buesing, Brian McWilliams, 2020, ICLR.

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

Benjamin Schrauwen, Robert A. Legenstein, Lars Buesing, 2008, NIPS.

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

Wulfram Gerstner, Claudia Clopath, Lars Buesing, 2008, PLoS Comput. Biol..

Value-driven Hindsight Modelling pdf

Fabio Viola, Doina Precup, David Silver, 2020, NeurIPS.

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

Andrew Jaegle, Nicolas Heess, Lars Buesing, 2020, ArXiv.

Combining Q-Learning and Search with Amortized Value Estimates pdf

Jessica B. Hamrick, Tobias Pfaff, Lars Buesing, 2020, ICLR.

Learning and Querying Fast Generative Models for Reinforcement Learning pdf

Fabio Viola, Demis Hassabis, Daan Wierstra, 2018, ArXiv.

Learning model-based planning from scratch pdf

Razvan Pascanu, Yujia Li, Oriol Vinyals, 2017, ArXiv.

A Spiking Neuron as Information Bottleneck

Wolfgang Maass, Lars Buesing, Lars Buesing, 2010, Neural Computation.

Neural scene representation and rendering

Koray Kavukcuoglu, Daan Wierstra, Karol Gregor, 2018, Science.

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

Adam M. Packer, Jakob H. Macke, Srinivas C. Turaga, 2013, NIPS.

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

Wolfgang Maass, Lars Buesing, Bernhard Nessler, 2013, PLoS Comput. Biol..

Counterfactual Credit Assignment in Model-Free Reinforcement Learning pdf

Fabio Viola, Marcus Hutter, Nicolas Heess, 2020, ArXiv.

Fast amortized inference of neural activity from calcium imaging data with variational autoencoders

Jakob H. Macke, Srinivas C. Turaga, Jinyao Yan, 2017, NIPS.

Clustered factor analysis of multineuronal spike data

John P. Cunningham, Liam Paninski, Lars Buesing, 2014, NIPS.

Inferring interactions between cell types from multiple calcium imaging snapshots of the same neural circuit

Jakob H. Macke, Srinivas C. Turaga, Lars Buesing, 2013 .

Towards combinatorial invariance for Kazhdan-Lusztig polynomials

Lars Buesing, Geordie Williamson, Petar Velivckovi'c, 2021, Representation Theory of the American Mathematical Society.

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

Razvan Pascanu, Brian McWilliams, Charles Blundell, 2022, ArXiv.

Counterfactual Credit Assignment in Model-Free Reinforcement Learning

Marcus Hutter, Nicolas Heess, Fabio Viola, 2020, ICML.

Making sense of raw input

Pushmeet Kohli, Marek J. Sergot, Lars Buesing, 2021, Artif. Intell..

Value-driven Hindsight Modelling pdf

Doina Precup, David Silver, Nicolas Heess, 2020, NeurIPS.

A Statistical Model of Shared Variability in the Songbird Auditory System

John P. Cunningham, Liam Paninski, Lars Buesing, 2017, bioRxiv.

Pointer Graph Networks pdf

Razvan Pascanu, Oriol Vinyals, Charles Blundell, 2020, NeurIPS.

Noisy Inputs In Vitro The Dynamical Response Properties of Neocortical Neurons to Temporally Modulated

Johannes Schemmel, Karlheinz Meier, Wulfram Gerstner, 2008 .