Nicolas Heess

According to our database1, Nicolas Heess authored at least 99 papers between 2009 and 2019.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2019
A Generalized Training Approach for Multiagent Learning.
CoRR, 2019

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control.
CoRR, 2019

Regularized Hierarchical Policies for Compositional Transfer in Robotics.
CoRR, 2019

Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces.
CoRR, 2019

Meta reinforcement learning as task inference.
CoRR, 2019

Meta-learning of Sequential Strategies.
CoRR, 2019

Information asymmetry in KL-regularized RL.
CoRR, 2019

Exploiting Hierarchy for Learning and Transfer in KL-regularized RL.
CoRR, 2019

The Termination Critic.
CoRR, 2019

Emergent Coordination Through Competition.
CoRR, 2019

Value constrained model-free continuous control.
CoRR, 2019

Credit Assignment Techniques in Stochastic Computation Graphs.
CoRR, 2019

Self-supervised Learning of Image Embedding for Continuous Control.
CoRR, 2019

Composing Entropic Policies using Divergence Correction.
Proceedings of the 36th International Conference on Machine Learning, 2019

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures.
Proceedings of the 7th International Conference on Learning Representations, 2019

Neural Probabilistic Motor Primitives for Humanoid Control.
Proceedings of the 7th International Conference on Learning Representations, 2019

Hierarchical Visuomotor Control of Humanoids.
Proceedings of the 7th International Conference on Learning Representations, 2019

Emergent Coordination Through Competition.
Proceedings of the 7th International Conference on Learning Representations, 2019

Information asymmetry in KL-regularized RL.
Proceedings of the 7th International Conference on Learning Representations, 2019

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search.
Proceedings of the 7th International Conference on Learning Representations, 2019

Observational Learning by Reinforcement Learning.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Credit Assignment Techniques in Stochastic Computation Graphs.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

The Termination Critic.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Relative Entropy Regularized Policy Iteration.
CoRR, 2018

Entropic Policy Composition with Generalized Policy Improvement and Divergence Correction.
CoRR, 2018

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures.
CoRR, 2018

Neural probabilistic motor primitives for humanoid control.
CoRR, 2018

Hierarchical visuomotor control of humanoids.
CoRR, 2018

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search.
CoRR, 2018

Maximum a Posteriori Policy Optimisation.
CoRR, 2018

Mix&Match - Agent Curricula for Reinforcement Learning.
CoRR, 2018

Relational inductive biases, deep learning, and graph networks.
CoRR, 2018

Graph networks as learnable physics engines for inference and control.
CoRR, 2018

Distributed Distributional Deterministic Policy Gradients.
CoRR, 2018

Learning by Playing - Solving Sparse Reward Tasks from Scratch.
CoRR, 2018

Reinforcement and Imitation Learning for Diverse Visuomotor Skills.
CoRR, 2018

Reinforcement and Imitation Learning for Diverse Visuomotor Skills.
Proceedings of the Robotics: Science and Systems XIV, 2018

Graph Networks as Learnable Physics Engines for Inference and Control.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning by Playing Solving Sparse Reward Tasks from Scratch.
Proceedings of the 35th International Conference on Machine Learning, 2018

Mix & Match Agent Curricula for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning an Embedding Space for Transferable Robot Skills.
Proceedings of the 6th International Conference on Learning Representations, 2018

Distributed Distributional Deterministic Policy Gradients.
Proceedings of the 6th International Conference on Learning Representations, 2018

Maximum a Posteriori Policy Optimisation.
Proceedings of the 6th International Conference on Learning Representations, 2018

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

Robust Imitation of Diverse Behaviors.
CoRR, 2017

FeUdal Networks for Hierarchical Reinforcement Learning.
CoRR, 2017

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards.
CoRR, 2017

Distral: Robust Multitask Reinforcement Learning.
CoRR, 2017

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation.
CoRR, 2017

Learning model-based planning from scratch.
CoRR, 2017

Learning human behaviors from motion capture by adversarial imitation.
CoRR, 2017

Filtering Variational Objectives.
CoRR, 2017

Particle Value Functions.
CoRR, 2017

Emergence of Locomotion Behaviours in Rich Environments.
CoRR, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
CoRR, 2017

Learning Hierarchical Information Flow with Recurrent Neural Modules.
CoRR, 2017

Distral: Robust multitask reinforcement learning.
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.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

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

Learning Hierarchical Information Flow with Recurrent Neural Modules.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Robust Imitation of Diverse Behaviors.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

FeUdal Networks for Hierarchical Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Particle Value Functions.
Proceedings of the 5th International Conference on Learning Representations, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Sample Efficient Actor-Critic with Experience Replay.
Proceedings of the 5th International Conference on Learning Representations, 2017

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
Sample Efficient Actor-Critic with Experience Replay.
CoRR, 2016

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
CoRR, 2016

Unsupervised Learning of 3D Structure from Images.
CoRR, 2016

Continuous control with deep reinforcement learning.
Proceedings of the 4th International Conference on Learning Representations, 2016

Learning and Transfer of Modulated Locomotor Controllers.
CoRR, 2016

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.
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

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Gradient Estimation Using Stochastic Computation Graphs.
CoRR, 2015

Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.
CoRR, 2015

Passing Expectation Propagation Messages with Kernel Methods.
CoRR, 2015

Learning Continuous Control Policies by Stochastic Value Gradients.
CoRR, 2015

Memory-based control with recurrent neural networks.
CoRR, 2015

Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Gradient Estimation Using Stochastic Computation Graphs.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Learning Continuous Control Policies by Stochastic Value Gradients.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
The Shape Boltzmann Machine: A Strong Model of Object Shape.
International Journal of Computer Vision, 2014

Recurrent Models of Visual Attention.
CoRR, 2014

Recurrent Models of Visual Attention.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Bayes-Adaptive Simulation-based Search with Value Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Deterministic Policy Gradient Algorithms.
Proceedings of the 31th International Conference on Machine Learning, 2014

Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Learning to Pass Expectation Propagation Messages.
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
Learning generative models of mid-level structure in natural images.
PhD thesis, 2012

Searching for objects driven by context.
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

Actor-Critic Reinforcement Learning with Energy-Based Policies.
Proceedings of the Tenth European Workshop on Reinforcement Learning, 2012

The Shape Boltzmann Machine: A strong model of object shape.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Learning a Generative Model of Images by Factoring Appearance and Shape.
Neural Computation, 2011

Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
CoRR, 2011

Multimodal Nonlinear Filtering Using Gauss-Hermite Quadrature.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Weakly Supervised Learning of Foreground-Background Segmentation Using Masked RBMs.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2009
Learning Generative Texture Models with extended Fields-of-Experts.
Proceedings of the British Machine Vision Conference, 2009


  Loading...