Pieter Abbeel

91

Papers

8,229

Total Citations

Papers (91)

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

NeurIPS 2016arXiv

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning

NeurIPS 2017arXiv

One-Shot Imitation Learning

NeurIPS 2017arXiv

Value Iteration Networks

NeurIPS 2016arXiv

Learning to Poke by Poking: Experiential Learning of Intuitive Physics

NeurIPS 2016arXiv

Learning Interactive Real-World Simulators

Backprop KF: Learning Discriminative Deterministic State Estimators

NeurIPS 2016arXiv

World Model on Million-Length Video And Language With Blockwise RingAttention

Video Language Planning

VIME: Variational Information Maximizing Exploration

NeurIPS 2016arXiv

Combinatorial Energy Learning for Image Segmentation

NeurIPS 2016arXiv

ElasticTok: Adaptive Tokenization for Image and Video

Prioritized Generative Replay

DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing

Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners

Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction

Gradient Estimation Using Stochastic Computation Graphs

NeurIPS 2015arXiv

Sim-to-Real 6D Object Pose Estimation via Iterative Self-Training for Robotic Bin Picking

Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis

VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models

Zero-Shot Text-Guided Object Generation With Dream Fields

Bottleneck Transformers for Visual Recognition

Cooperative Inverse Reinforcement Learning

NeurIPS 2016arXiv

Inverse Reward Design

NeurIPS 2017arXiv

Learning to Model the World With Language

Position: Video as the New Language for Real-World Decision Making

Visual Representation Learning with Stochastic Frame Prediction

Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings

Learning a Diffusion Model Policy from Rewards via Q-Score Matching

Masked Autoencoding for Scalable and Generalizable Decision Making

Deep Hierarchical Planning from Pixels

On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning

Unsupervised Reinforcement Learning with Contrastive Intrinsic Control

Chain of Thought Imitation with Procedure Cloning

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?

Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment

Blockwise Parallel Transformers for Large Context Models

Learning Universal Policies via Text-Guided Video Generation

Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration

Video Prediction Models as Rewards for Reinforcement Learning

AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

Alpha-Beta Divergences Discover Micro and Macro Structures in Data

Trust Region Policy Optimization

Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization

Benchmarking Deep Reinforcement Learning for Continuous Control

Constrained Policy Optimization

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Reinforcement Learning with Deep Energy-Based Policies

Prediction and Control with Temporal Segment Models

PixelSNAIL: An Improved Autoregressive Generative Model

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings

Automatic Goal Generation for Reinforcement Learning Agents

Latent Space Policies for Hierarchical Reinforcement Learning

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules

Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning

Learning Plannable Representations with Causal InfoGAN

Meta-Reinforcement Learning of Structured Exploration Strategies

Evolved Policy Gradients

The Importance of Sampling inMeta-Reinforcement Learning

Compositional Plan Vectors

Evaluating Protein Transfer Learning with TAPE

Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies

Geometry-Aware Neural Rendering

Goal-conditioned Imitation Learning

Guided Meta-Policy Search

On the Utility of Learning about Humans for Human-AI Coordination

Compression with Flows via Local Bits-Back Coding

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

AvE: Assistance via Empowerment

Sparse Graphical Memory for Robust Planning

Denoising Diffusion Probabilistic Models

Automatic Curriculum Learning through Value Disagreement

Generalized Hindsight for Reinforcement Learning

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning

Reinforcement Learning with Augmented Data

Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL

Teachable Reinforcement Learning via Advice Distillation

Decision Transformer: Reinforcement Learning via Sequence Modeling

Behavior From the Void: Unsupervised Active Pre-Training

Reinforcement Learning with Latent Flow

Mastering Atari Games with Limited Data

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings

Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions