Nicholas Rhinehart

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

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Achievements

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🗺️ Taxonomy Completionist (33) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🧬 Topic Evolution 🤝 Dynamic Duo (11) ⚡ Prolific Year · Productive 🔥 Unstoppable · Bronze ❓ The Questioner (2) 💎 Century Club · Bronze 🚀 Conference Pioneer 🗃️ Keyword Collector (92)

Venues

ICLR (6) CoRL (5) ECCV (3) NeurIPS (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)

Research topics

Artificial Intelligence (16) Core AI (16) Machine Learning (8) Deep Learning (6) Computer Vision (5) Reinforcement Learning (5) Learning Types · Machine Learning (5) Methods (5) Analysis (3) Domain-Specific (3) Optimization & Theory (3) Learning Types · Deep Learning (2) Models (2) Robotics (1) Application Areas (1)

Keywords

autonomous driving (3) imitation learning (3) reinforcement learning (3) robotic manipulation (2) trajectory prediction (2) contingency planning (2) egocentric vision (2) policy gradient (1) information bottleneck (1) action recognition (1) variational inference (1) scene understanding (1) domain generalization (1) epistemic uncertainty (1) offline reinforcement learning (1) visual navigation (1) robotic navigation (1) continual learning (1) future prediction (1) deep reinforcement learning (1)

Papers

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