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Trevor Darrell

118 papers hereh-index 158231.1k citations630 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author62
  • last author47

Across the 109 of 118 papers where every author was matched, so the position is known.

fields
  • cs.CV79
  • cs.LG23
  • cs.RO6
  • cs.CL5
  • cs.AI4
  • stat.ML1
same name
  • Trevor Darrell — 44 papers
  • Trevor Darrell — 2 papers
  • Trevor Darrell — 1 paper
  • Trevor Darrell — 1 paper
  • Trevor Darrell — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122022
most citedCyCADA: Cycle-Consistent Adversarial Domain Adaptation

630 citations · 2.3k across the 46 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2018

Modular Architecture for StarCraft II with Deep Reinforcement Learning

Dennis Lee, Haoran Tang, Jeffrey O Zhang +3

We present a novel modular architecture for StarCraft II AI. The architecture splits responsibilities between multiple modules that each control one aspect of the game, such as bui…

cs.AI2018

Deep Object-Centric Policies for Autonomous Driving

Dequan Wang, Coline Devin, Qi-Zhi Cai +2

While learning visuomotor skills in an end-to-end manner is appealing, deep neural networks are often uninterpretable and fail in surprising ways. For robotics tasks, such as auton…

cs.AI2018

Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +4

Deep models that are both effective and explainable are desirable in many settings; prior explainable models have been unimodal, offering either image-based visualization of attent…

cs.AI2018

Reinforcement Learning from Imperfect Demonstrations

Yang Gao, Huazhe Xu, Ji Lin +3

Robust real-world learning should benefit from both demonstrations and interactions with the environment. Current approaches to learning from demonstration and reward perform super…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.