Lista de obras - Sergey Levine - Dominio Público Uruguay

Backprop KF: Learning Discriminative Deterministic State Estimators ⬇️

artículo científico publicado en 2016

Causal Confusion in Imitation Learning ⬇️

artículo científico publicado en 2019

Compositional Plan Vectors ⬇️

artículo científico publicado en 2019

Conservative Q-Learning for Offline Reinforcement Learning ⬇️

artículo científico publicado en 2020

Continual Learning of Control Primitives : Skill Discovery via Reset-Games ⬇️

artículo científico publicado en 2020

Data-Efficient Hierarchical Reinforcement Learning ⬇️

scholarly article by Ofir Nachum et al published 2018 in Advances in Neural Information Processing Systems 31

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models ⬇️

DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction ⬇️

scholarly article by Aviral Kumar et al published November 2020 in Advances in Neural Information Processing Systems 33

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning ⬇️

artículo científico publicado en 2017

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design ⬇️

artículo científico publicado en 2020

End-to-End Training of Deep Visuomotor Policies

artículo científico publicado en 2016

Feature Construction for Inverse Reinforcement Learning ⬇️

scholarly article by Sergey Levine et al published 2010 in Advances in Neural Information Processing Systems 23

Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction ⬇️

artículo científico publicado en 2020

Gradient Surgery for Multi-Task Learning ⬇️

artículo científico publicado en 2020

Guided Meta-Policy Search ⬇️

Guided Policy Search via Approximate Mirror Descent ⬇️

artículo científico publicado en 2016

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning ⬇️

Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics ⬇️

artículo científico publicado en 2014

Learning to Poke by Poking: Experiential Learning of Intuitive Physics ⬇️

artículo científico publicado en 2016

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors ⬇️

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies ⬇️

MOPO: Model-based Offline Policy Optimization ⬇️

artículo científico publicado en 2020

Meta-Learning with Implicit Gradients ⬇️

Meta-Reinforcement Learning of Structured Exploration Strategies ⬇️

scholarly article by Abhishek Gupta et al published 2018 in Advances in Neural Information Processing Systems 31

Model Inversion Networks for Model-Based Optimization ⬇️

artículo científico publicado en 2020

Nonlinear Inverse Reinforcement Learning with Gaussian Processes ⬇️

artículo científico publicado en 2011

Off-Policy Evaluation via Off-Policy Classification ⬇️

One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL ⬇️

Planning with Goal-Conditioned Policies ⬇️

artículo científico publicado en 2019

Probabilistic Model-Agnostic Meta-Learning ⬇️

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement ⬇️

artículo científico publicado en 2020

Search on the Replay Buffer: Bridging Planning and Reinforcement Learning ⬇️

artículo científico publicado en 2019

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction ⬇️

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model ⬇️

artículo científico publicado en 2020

Unsupervised Curricula for Visual Meta-Reinforcement Learning ⬇️

scholarly article by Allan Jabri et al published 2019 in Advances in Neural Information Processing Systems 32

Unsupervised Learning for Physical Interaction through Video Prediction ⬇️

artículo científico publicado en 2016

Value Iteration Networks

scholarly article

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition ⬇️

Variational Policy Search via Trajectory Optimization ⬇️

Visual Memory for Robust Path Following ⬇️

Visual Reinforcement Learning with Imagined Goals ⬇️

scholarly article by Ashvin V. Nair et al published 2018 in Advances in Neural Information Processing Systems 31

Wasserstein Dependency Measure for Representation Learning ⬇️

artículo científico publicado en 2019

When to Trust Your Model: Model-Based Policy Optimization ⬇️

article by Michael Janner et al published 2019 in Advances in Neural Information Processing Systems 32

Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior ⬇️

article

Lista de obras de Sergey Levine

Backprop KF: Learning Discriminative Deterministic State Estimators ⬇️

Causal Confusion in Imitation Learning ⬇️

Compositional Plan Vectors ⬇️

Conservative Q-Learning for Offline Reinforcement Learning ⬇️

Continual Learning of Control Primitives : Skill Discovery via Reset-Games ⬇️

Data-Efficient Hierarchical Reinforcement Learning ⬇️

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models ⬇️

DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction ⬇️

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning ⬇️

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design ⬇️

End-to-End Training of Deep Visuomotor Policies

Feature Construction for Inverse Reinforcement Learning ⬇️

Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction ⬇️

Gradient Surgery for Multi-Task Learning ⬇️

Guided Meta-Policy Search ⬇️

Guided Policy Search via Approximate Mirror Descent ⬇️

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning ⬇️

Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics ⬇️

Learning to Poke by Poking: Experiential Learning of Intuitive Physics ⬇️

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors ⬇️

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies ⬇️

MOPO: Model-based Offline Policy Optimization ⬇️

Meta-Learning with Implicit Gradients ⬇️

Meta-Reinforcement Learning of Structured Exploration Strategies ⬇️

Model Inversion Networks for Model-Based Optimization ⬇️

Nonlinear Inverse Reinforcement Learning with Gaussian Processes ⬇️

Off-Policy Evaluation via Off-Policy Classification ⬇️

One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL ⬇️

Planning with Goal-Conditioned Policies ⬇️

Probabilistic Model-Agnostic Meta-Learning ⬇️

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement ⬇️

Search on the Replay Buffer: Bridging Planning and Reinforcement Learning ⬇️

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction ⬇️

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model ⬇️

Unsupervised Curricula for Visual Meta-Reinforcement Learning ⬇️

Unsupervised Learning for Physical Interaction through Video Prediction ⬇️

Value Iteration Networks

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition ⬇️

Variational Policy Search via Trajectory Optimization ⬇️

Visual Memory for Robust Path Following ⬇️

Visual Reinforcement Learning with Imagined Goals ⬇️

Wasserstein Dependency Measure for Representation Learning ⬇️

When to Trust Your Model: Model-Based Policy Optimization ⬇️

Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior ⬇️