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researcher

Henrik I. Christensen

4 papers hereh-index 10417 citations14 works total

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

author position
  • last author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1
  • cs.RO1
same name
  • Henrik I. Christensen — 6 papers
  • Henrik I. Christensen — 6 papers, h 7
  • Henrik I. Christensen — 6 papers, h 4
  • Henrik I. Christensen — 6 papers, h 1
  • Henrik I. Christensen — 6 papers, h 3
  • Henrik I. Christensen — 6 papers, h 3

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
20192023
most citedHow to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?

22 citations · 23 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 1 cited

FashionNTM: Multi-turn Fashion Image Retrieval via Cascaded Memory

Anwesan Pal, Sahil Wadhwa, Ayush Jaiswal +5

Multi-turn textual feedback-based fashion image retrieval focuses on a real-world setting, where users can iteratively provide information to refine retrieval results until they fi…

cs.RO2021

Single RGB-D Camera Teleoperation for General Robotic Manipulation

Quan Vuong, Yuzhe Qin, Runlin Guo +3

We propose a teleoperation system that uses a single RGB-D camera as the human motion capture device. Our system can perform general manipulation tasks such as cloth folding, hamme…

cs.LG2019

Multi-task Batch Reinforcement Learning with Metric Learning

Jiachen Li, Quan Vuong, Shuang Liu +5

We tackle the Multi-task Batch Reinforcement Learning problem. Given multiple datasets collected from different tasks, we train a multi-task policy to perform well in unseen tasks…

cs.LG2019★ 22 cited

How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?

Quan Vuong, Sharad Vikram, Hao Su +2

Recently, reinforcement learning (RL) algorithms have demonstrated remarkable success in learning complicated behaviors from minimally processed input. However, most of this succes…

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