Rowan McAllister
10 papers · 2017–2024 · 6 venues · across top CS/AI venues
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Keywords
autonomous vehicle
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imitation learning
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autonomous driving
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model-based reinforcement learning
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uncertainty quantification
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epistemic uncertainty
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sample efficiency
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gaussian process
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belief state
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partially observable markov decision process
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state estimation
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probabilistic model
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distribution shift
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pomdp
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off-policy learning
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trajectory forecasting
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neural radiance field
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reinforcement learning
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Papers
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting
ECCV 2024
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
NeurIPS 2023
S2Net: Stochastic Sequential Pointcloud Forecasting
ECCV 2022
Outcome-Driven Reinforcement Learning via Variational Inference
NeurIPS 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
PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings
ICCV 2019
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
NeurIPS 2018
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning
IJCAI 2017
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs
NeurIPS 2017