← Authors

Nicholas Rhinehart

22 papers · 2016–2024 · 7 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (7) πŸ—ΊοΈ Taxonomy Completionist (26) 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (13) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (8) 🀝 Dynamic Duo (11) 🧬 Topic Evolution πŸ”₯ Unstoppable (9) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (64) ❓ The Questioner (2) πŸ’Ž Century Club (22)

Conferences

ICLR (6) CORL (5) ECCV (3) NIPS (3) CVPR (2) ICCV (2) ICML (1)

Top co-authors

Sergey Levine (11) Kris M. Kitani (8) Rowan McAllister (5) Kris Kitani (3) Glen Berseth (2) Chelsea Finn (2) Joseph E Gonzalez (2) Dhruv Shah (2) Charles Packer (2) Xinshuo Weng (2)

Keywords

egocentric vision (2) imitation learning (2) trajectory prediction (2) autonomous driving (2) robotic navigation (1) robotic manipulation (1) offline reinforcement learning (1) activity recognition (1) information bottleneck (1) scene understanding (1) epistemic uncertainty (1) variational inference (1) visual navigation (1) domain generalization (1) action recognition (1) future prediction (1) activity forecasting (1) trajectory forecasting (1) continual learning (1) deep reinforcement learning (1)

Papers

CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting ECCV 2024
The Waymo Open Sim Agents Challenge NIPS 2023
S2Net: Stochastic Sequential Pointcloud Forecasting ECCV 2022
Offline Reinforcement Learning for Visual Navigation CORL 2022
Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty CORL 2022
Rapid Exploration for Open-World Navigation with Latent Goal Models CORL 2021
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments ICLR 2021
Information is Power: Intrinsic Control via Information Capture NIPS 2021
Conservative Safety Critics for Exploration ICLR 2021
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning ICLR 2021
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? ICML 2020
Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting CORL 2020
Generative Hybrid Representations for Activity Forecasting With No-Regret Learning CVPR 2020
Deep Imitative Models for Flexible Inference, Planning, and Control ICLR 2020
Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information ICLR 2019
PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings ICCV 2019
R2P2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting ECCV 2018
N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning ICLR 2018
Learning Neural Parsers with Deterministic Differentiable Imitation Learning CORL 2018
First-Person Activity Forecasting With Online Inverse Reinforcement Learning ICCV 2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks NIPS 2017
Learning Action Maps of Large Environments via First-Person Vision CVPR 2016