Danilo J. Rezende

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 35

Top Topics

Bayesian Modeling

Information Bottleneck

Reinforcement Learning

Top Venues

Frontiers Comput. Neurosci.

Publications

Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. CoRR (2024)
SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young
Scaling Instructable Agents Across Many Simulated Worlds. CoRR (2024)
Ryan Abbott, Aleksandar Botev, Denis Boyda, Daniel C. Hackett, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Applications of flow models to the generation of correlated lattice QCD ensembles. CoRR (2024)
Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew Kyle Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo J. Rezende, Daniel Zoran
Combining Behaviors with the Successor Features Keyboard. CoRR (2023)
Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Alexander G. de G. Matthews, Sébastien Racanière, Ali Razavi, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Normalizing flows for lattice gauge theory in arbitrary space-time dimension. CoRR (2023)
Pol Moreno, Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Rosália G. Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, Danilo J. Rezende
Laser: Latent Set Representations for 3D Generative Modeling. CoRR (2023)
Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR (2023)
Kyle Cranmer, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Phiala E. Shanahan
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics. CoRR (2023)
Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Alexander G. de G. Matthews, Sébastien Racanière, Ali Razavi, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Aspects of scaling and scalability for flow-based sampling of lattice QCD. CoRR (2022)
Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Julian M. Urban
Flow-based sampling in the lattice Schwinger model at criticality. CoRR (2022)
Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo J. Rezende, Dan Rosenbaum
From data to functa: Your data point is a function and you should treat it like one. CoRR (2022)
Ryan Abbott, Michael S. Albergo, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Fernando Romero-López, Phiala E. Shanahan, Betsy Tian, Julian M. Urban
Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions. CoRR (2022)
Irina Higgins, Sébastien Racanière, Danilo J. Rezende
Symmetry-Based Representations for Artificial and Biological General Intelligence. Frontiers Comput. Neurosci. 16 (2022)
Irina Higgins, Sébastien Racanière, Danilo J. Rezende
Symmetry-Based Representations for Artificial and Biological General Intelligence. CoRR (2022)
Alexander G. de G. Matthews, Michael Arbel, Danilo J. Rezende, Arnaud Doucet
Continual Repeated Annealed Flow Transport Monte Carlo. CoRR (2022)
Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo J. Rezende
NeRF-VAE: A Geometry Aware 3D Scene Generative Model. CoRR (2021)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR (2021)
Daniel Zoran, Rishabh Kabra, Alexander Lerchner, Danilo J. Rezende
PARTS: Unsupervised segmentation with slots, attention and independence maximization. ICCV (2021)
Michael S. Albergo, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Julian M. Urban, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Phiala E. Shanahan
Flow-based sampling for fermionic lattice field theories. CoRR (2021)
Danilo J. Rezende, Sébastien Racanière
Implicit Riemannian Concave Potential Maps. CoRR (2021)
Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende
Amortized learning of neural causal representations. CoRR (2020)
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
Causally Correct Partial Models for Reinforcement Learning. CoRR (2020)
Adam R. Kosiorek, Hyunjik Kim, Danilo J. Rezende
Conditional Set Generation with Transformers. CoRR (2020)
Slava Voloshynovskiy, Olga Taran, Mouad Kondah, Taras Holotyak, Danilo J. Rezende
Variational Information Bottleneck for Semi-Supervised Classification. Entropy 22 (9) (2020)
Peter Toth, Danilo J. Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins
Hamiltonian Generative Networks. ICLR (2020)
David Pfau, Danilo J. Rezende
Integrable Nonparametric Flows. CoRR (2020)
Alex Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo J. Rezende
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents. CoRR (2019)
Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy A. Mann, Danilo J. Rezende
Beyond Greedy Ranking: Slate Optimization via List-CVAE. ICLR (Poster) (2019)
Irina Higgins, David Amos, David Pfau, Sébastien Racanière, Loïc Matthey, Danilo J. Rezende, Alexander Lerchner
Towards a Definition of Disentangled Representations. CoRR (2018)
Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo J. Rezende, Oriol Vinyals, Nando de Freitas
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. ICLR (Poster) (2018)
Dan Rosenbaum, Frederic Besse, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami
Learning models for visual 3D localization with implicit mapping. CoRR (2018)
Marta Garnelo, Dan Rosenbaum, Chris J. Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo J. Rezende, S. M. Ali Eslami
Conditional Neural Processes. CoRR (2018)
Ray Jiang, Sven Gowal, Timothy A. Mann, Danilo J. Rezende
Optimizing Slate Recommendations via Slate-CVAE. CoRR (2018)
Marta Garnelo, Jonathan Schwarz, Dan Rosenbaum, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami, Yee Whye Teh
Neural Processes. CoRR (2018)
Ananya Kumar, S. M. Ali Eslami, Danilo J. Rezende, Marta Garnelo, Fabio Viola, Edward Lockhart, Murray Shanahan
Consistent Generative Query Networks. CoRR (2018)