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Jiaming Guo

7 papers here

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

author position
  • first author2
  • middle author5

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL1
  • cs.CV1
  • eess.IV1
ORCID 0000-0002-4774-2074
same name
  • Jiaming Guo — 7 papers, h 10
  • Jiaming Guo — 4 papers
  • Jiaming Guo — 2 papers
  • Jiaming Guo — 1 paper, h 16

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

most citedAsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions

2 citations · 7 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023★ 1 cited

Context Shift Reduction for Offline Meta-Reinforcement Learning

Yunkai Gao, Rui Zhang, Jiaming Guo +10

Offline meta-reinforcement learning (OMRL) utilizes pre-collected offline datasets to enhance the agent's generalization ability on unseen tasks. However, the context shift problem…

cs.LG2023★ 1 cited

Efficient Symbolic Policy Learning with Differentiable Symbolic Expression

Jiaming Guo, Rui Zhang, Shaohui Peng +8

Deep reinforcement learning (DRL) has led to a wide range of advances in sequential decision-making tasks. However, the complexity of neural network policies makes it difficult to…

cs.LG2023★ 1 cited

Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning

Siming Lan, Rui Zhang, Qi Yi +10

In the field of multi-task reinforcement learning, the modular principle, which involves specializing functionalities into different modules and combining them appropriately, has b…

cs.LG2023★ 1 cited

Conceptual Reinforcement Learning for Language-Conditioned Tasks

Shaohui Peng, Xing Hu, Rui Zhang +7

Despite the broad application of deep reinforcement learning (RL), transferring and adapting the policy to unseen but similar environments is still a significant challenge. Recentl…

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