Danilo Jimenez Rezende

Orcid: 0000-0003-3184-8509

Affiliations:
  • Google


According to our database1, Danilo Jimenez Rezende authored at least 73 papers between 2011 and 2024.

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Bibliography

2024
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving.
CoRR, 2024

Scaling Instructable Agents Across Many Simulated Worlds.
CoRR, 2024

Applications of flow models to the generation of correlated lattice QCD ensembles.
CoRR, 2024

2023
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics.
CoRR, 2023

Normalizing flows for lattice gauge theory in arbitrary space-time dimension.
CoRR, 2023

DiscoGen: Learning to Discover Gene Regulatory Networks.
CoRR, 2023

Laser: Latent Set Representations for 3D Generative Modeling.
CoRR, 2023

Combining Behaviors with the Successor Features Keyboard.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Induce Causal Structure.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Symmetry-Based Representations for Artificial and Biological General Intelligence.
Frontiers Comput. Neurosci., 2022

Aspects of scaling and scalability for flow-based sampling of lattice QCD.
CoRR, 2022

Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions.
CoRR, 2022

Learning to Induce Causal Structure.
CoRR, 2022

Flow-based sampling in the lattice Schwinger model at criticality.
CoRR, 2022

From data to functa: Your data point is a function and you should treat it like one.
CoRR, 2022

Continual Repeated Annealed Flow Transport Monte Carlo.
Proceedings of the International Conference on Machine Learning, 2022

From data to functa: Your data point is a function and you can treat it like one.
Proceedings of the International Conference on Machine Learning, 2022

2021
Normalizing Flows for Probabilistic Modeling and Inference.
J. Mach. Learn. Res., 2021

Implicit Riemannian Concave Potential Maps.
CoRR, 2021

Flow-based sampling for fermionic lattice field theories.
CoRR, 2021

Introduction to Normalizing Flows for Lattice Field Theory.
CoRR, 2021

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

NeRF-VAE: A Geometry Aware 3D Scene Generative Model.
Proceedings of the 38th International Conference on Machine Learning, 2021

PARTS: Unsupervised segmentation with slots, attention and independence maximization.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Variational Information Bottleneck for Semi-Supervised Classification.
Entropy, 2020

Integrable Nonparametric Flows.
CoRR, 2020

Amortized learning of neural causal representations.
CoRR, 2020

Sampling using SU(N) gauge equivariant flows.
CoRR, 2020

Conditional Set Generation with Transformers.
CoRR, 2020

Neural Communication Systems with Bandwidth-limited Channel.
CoRR, 2020

Equivariant flow-based sampling for lattice gauge theory.
CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.
CoRR, 2020

Normalizing Flows on Tori and Spheres.
Proceedings of the 37th International Conference on Machine Learning, 2020

Hamiltonian Generative Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Information bottleneck through variational glasses.
CoRR, 2019

Equivariant Hamiltonian Flows.
CoRR, 2019

A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities.
CoRR, 2019

Towards Interpretable Reinforcement Learning Using Attention Augmented Agents.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Shaping Belief States with Generative Environment Models for RL.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Beyond Greedy Ranking: Slate Optimization via List-CVAE.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Towards a Definition of Disentangled Representations.
CoRR, 2018

Taming VAEs.
CoRR, 2018

Learning models for visual 3D localization with implicit mapping.
CoRR, 2018

Consistent Generative Query Networks.
CoRR, 2018

Neural Processes.
CoRR, 2018

Unsupervised Predictive Memory in a Goal-Directed Agent.
CoRR, 2018

Optimizing Slate Recommendations via Slate-CVAE.
CoRR, 2018

Learning and Querying Fast Generative Models for Reinforcement Learning.
CoRR, 2018

A Probabilistic U-Net for Segmentation of Ambiguous Images.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Conditional Neural Processes.
Proceedings of the 35th International Conference on Machine Learning, 2018

Generative Temporal Models with Spatial Memory for Partially Observed Environments.
Proceedings of the 35th International Conference on Machine Learning, 2018

Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.
CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.
CoRR, 2017

Generative Temporal Models with Memory.
CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Memory Addressing in Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Intrinsic Control.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Normalizing Flows on Riemannian Manifolds.
CoRR, 2016

Unsupervised Learning of 3D Structure from Images.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Towards Conceptual Compression.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Interaction Networks for Learning about Objects, Relations and Physics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

One-Shot Generalization in Deep Generative Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Variational Inference for Monte Carlo Objectives.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Towards Principled Unsupervised Learning.
CoRR, 2015

Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Variational Inference with Normalizing Flows.
Proceedings of the 32nd International Conference on Machine Learning, 2015

DRAW: A Recurrent Neural Network For Image Generation.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Stochastic variational learning in recurrent spiking networks.
Frontiers Comput. Neurosci., 2014

Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models.
CoRR, 2014

Semi-supervised Learning with Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Stochastic Backpropagation and Approximate Inference in Deep Generative Models.
Proceedings of the 31th International Conference on Machine Learning, 2014

2011
Variational Learning for Recurrent Spiking Networks.
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


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