Danilo Jimenez Rezende

66 papers A* 18Journal 38Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Exploring exploration with foundation agents in interactive environments. Trans. Mach. Learn. Res. Daniel P. Sawyer, Nan Rosemary Ke, Hubert Soyer, Martin Engelcke, John Reid, David P. Reichert, Drew A. Hudson, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P. Lillicrap, Michael Curtis Mozer, Jane X. Wang
2024	J	`jnl`	Can foundation models actively gather information in interactive environments to test hypotheses? CoRR Nan Rosemary Ke, Danny P. Sawyer, Hubert Soyer, Martin Engelcke, David P. Reichert, Drew A. Hudson, John Reid, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P. Lillicrap, Michael Mozer, Jane X. Wang
2024	A*	`conf`	Generative Hierarchical Materials Search. NeurIPS Sherry Yang, Simon L. Batzner, Ruiqi Gao, Muratahan Aykol, Alexander L. Gaunt, Brendan McMorrow, Danilo Jimenez Rezende, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk
2024	A*	`conf`	Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. NeurIPS Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora
2023	A*	`conf`	Combining Behaviors with the Successor Features Keyboard. NeurIPS Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran
2023	A*	`conf`	Learning to Induce Causal Structure. ICLR Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
2022	A*	`conf`	Continual Repeated Annealed Flow Transport Monte Carlo. ICML Alexander G. de G. Matthews, Michael Arbel, Danilo Jimenez Rezende, Arnaud Doucet
2022	A*	`conf`	From data to functa: Your data point is a function and you can treat it like one. ICML Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo Jimenez Rezende, Dan Rosenbaum
2022	J	`jnl`	Learning to Induce Causal Structure. CoRR Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
2021	J	`jnl`	Introduction to Normalizing Flows for Lattice Field Theory. CoRR Michael S. Albergo, Denis Boyda, Daniel C. Hackett, Gurtej Kanwar, Kyle Cranmer, Sébastien Racanière, Danilo Jimenez Rezende, Phiala E. Shanahan
2021	A*	`conf`	NeRF-VAE: A Geometry Aware 3D Scene Generative Model. ICML Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo Jimenez Rezende
2021	J	`jnl`	Normalizing Flows for Probabilistic Modeling and Inference. J. Mach. Learn. Res. George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
2021	—	`conf`	Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal
2020	J	`jnl`	Equivariant flow-based sampling for lattice gauge theory. CoRR Gurtej Kanwar, Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Sébastien Racanière, Danilo Jimenez Rezende, Phiala E. Shanahan
2020	J	`jnl`	Neural Communication Systems with Bandwidth-limited Channel. CoRR Karen Ullrich, Fabio Viola, Danilo Jimenez Rezende
2020	A*	`conf`	Normalizing Flows on Tori and Spheres. ICML Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer
2020	J	`jnl`	Normalizing Flows on Tori and Spheres. CoRR Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer
2020	J	`jnl`	Sampling using SU(N) gauge equivariant flows. CoRR Denis Boyda, Gurtej Kanwar, Sébastien Racanière, Danilo Jimenez Rezende, Michael S. Albergo, Kyle Cranmer, Daniel C. Hackett, Phiala E. Shanahan
2019	J	`jnl`	A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities. CoRR Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein, Danilo Jimenez Rezende, S. M. Ali Eslami, Pushmeet Kohli, Andrew Zisserman, Olaf Ronneberger
2019	J	`jnl`	Equivariant Hamiltonian Flows. CoRR Danilo Jimenez Rezende, Sébastien Racanière, Irina Higgins, Peter Toth
2019	J	`jnl`	Hamiltonian Generative Networks. CoRR Peter Toth, Danilo Jimenez Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins
2019	J	`jnl`	Information bottleneck through variational glasses. CoRR Slava Voloshynovskiy, Mouad Kondah, Shideh Rezaeifar, Olga Taran, Taras Holotyak, Danilo Jimenez Rezende
2019	J	`jnl`	Normalizing Flows for Probabilistic Modeling and Inference. CoRR George Papamakarios, Eric T. Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
2019	A*	`conf`	Shaping Belief States with Generative Environment Models for RL. NeurIPS Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aäron van den Oord
2019	J	`jnl`	Shaping Belief States with Generative Environment Models for RL. CoRR Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aäron van den Oord
2019	A*	`conf`	Towards Interpretable Reinforcement Learning Using Attention Augmented Agents. NeurIPS Alexander Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo Jimenez Rezende
2018	A*	`conf`	A Probabilistic U-Net for Segmentation of Ambiguous Images. NeurIPS Simon Kohl, Bernardino Romera-Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph R. Ledsam, Klaus H. Maier-Hein, S. M. Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger
2018	J	`jnl`	A Probabilistic U-Net for Segmentation of Ambiguous Images. CoRR Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph R. Ledsam, Klaus H. Maier-Hein, S. M. Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger
2018	A*	`conf`	Conditional Neural Processes. ICML Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Jimenez Rezende, S. M. Ali Eslami
2018	A*	`conf`	Generative Temporal Models with Spatial Memory for Partially Observed Environments. ICML Marco Fraccaro, Danilo Jimenez Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola
2018	J	`jnl`	Generative Temporal Models with Spatial Memory for Partially Observed Environments. CoRR Marco Fraccaro, Danilo Jimenez Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola
2018	J	`jnl`	Learning and Querying Fast Generative Models for Reinforcement Learning. CoRR 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
2018	J	`jnl`	Taming VAEs. CoRR Danilo Jimenez Rezende, Fabio Viola
2018	J	`jnl`	Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack W. Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Jimenez Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matthew M. Botvinick, Demis Hassabis, Timothy P. Lillicrap
2017	J	`jnl`	Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR Matthew M. Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis
2017	J	`jnl`	Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. CoRR Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Jimenez Rezende, Oriol Vinyals, Nando de Freitas
2017	J	`jnl`	Generative Temporal Models with Memory. CoRR Mevlana Gemici, Chia-Chun Hung, Adam Santoro, Greg Wayne, Shakir Mohamed, Danilo Jimenez Rezende, David Amos, Timothy P. Lillicrap
2017	—	`conf`	Imagination-Augmented Agents for Deep Reinforcement Learning. NIPS 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
2017	J	`jnl`	Imagination-Augmented Agents for Deep Reinforcement Learning. CoRR 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
2017	—	`conf`	Variational Intrinsic Control. ICLR (Workshop) Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra
2017	—	`conf`	Variational Memory Addressing in Generative Models. NIPS Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende
2017	J	`jnl`	Variational Memory Addressing in Generative Models. CoRR Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende
2016	—	`conf`	Interaction Networks for Learning about Objects, Relations and Physics. NIPS Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, Koray Kavukcuoglu
2016	J	`jnl`	Interaction Networks for Learning about Objects, Relations and Physics. CoRR Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, Koray Kavukcuoglu
2016	J	`jnl`	Normalizing Flows on Riemannian Manifolds. CoRR Mevlana C. Gemici, Danilo Jimenez Rezende, Shakir Mohamed
2016	A*	`conf`	One-Shot Generalization in Deep Generative Models. ICML Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
2016	J	`jnl`	One-Shot Generalization in Deep Generative Models. CoRR Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
2016	—	`conf`	Towards Conceptual Compression. NIPS Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra
2016	J	`jnl`	Towards Conceptual Compression. CoRR Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra
2016	—	`conf`	Unsupervised Learning of 3D Structure from Images. NIPS Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess
2016	J	`jnl`	Unsupervised Learning of 3D Structure from Images. CoRR Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess
2016	A*	`conf`	Variational Inference for Monte Carlo Objectives. ICML Andriy Mnih, Danilo Jimenez Rezende
2016	J	`jnl`	Variational Intrinsic Control. CoRR Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra
2016	J	`jnl`	Variational inference for Monte Carlo objectives. CoRR Andriy Mnih, Danilo Jimenez Rezende
2015	A*	`conf`	DRAW: A Recurrent Neural Network For Image Generation. ICML Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra
2015	J	`jnl`	Towards Principled Unsupervised Learning. CoRR Ilya Sutskever, Rafal Józefowicz, Karol Gregor, Danilo Jimenez Rezende, Timothy P. Lillicrap, Oriol Vinyals
2015	A*	`conf`	Variational Inference with Normalizing Flows. ICML Danilo Jimenez Rezende, Shakir Mohamed
2015	J	`jnl`	Variational Inference with Normalizing Flows. CoRR Danilo Jimenez Rezende, Shakir Mohamed
2015	—	`conf`	Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. NIPS Shakir Mohamed, Danilo Jimenez Rezende
2015	J	`jnl`	Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. CoRR Shakir Mohamed, Danilo Jimenez Rezende
2014	J	`jnl`	Semi-Supervised Learning with Deep Generative Models. CoRR Diederik P. Kingma, Danilo Jimenez Rezende, Shakir Mohamed, Max Welling
2014	—	`conf`	Semi-supervised Learning with Deep Generative Models. NIPS Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling
2014	J	`jnl`	Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models. CoRR Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
2014	A*	`conf`	Stochastic Backpropagation and Approximate Inference in Deep Generative Models. ICML Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
2014	J	`jnl`	Stochastic variational learning in recurrent spiking networks. Frontiers Comput. Neurosci. Danilo Jimenez Rezende, Wulfram Gerstner
2011	—	`conf`	Variational Learning for Recurrent Spiking Networks. NIPS Danilo Jimenez Rezende, Daan Wierstra, Wulfram Gerstner