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Po-Han Chiang

3 papers here

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

author position
  • first author1
  • middle author2

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

fields
  • cs.LG3

identity via Semantic Scholar / OpenAlex

most citedNever Forget: Balancing Exploration and Exploitation via Learning Optical Flow

9 citations · 12 across the 2 of their papers we have counts for

collaborators

3 papers

cs.LG2020★ 3 cited

Mixture of Step Returns in Bootstrapped DQN

Po-Han Chiang, Hsuan-Kung Yang, Zhang-Wei Hong +1

The concept of utilizing multi-step returns for updating value functions has been adopted in deep reinforcement learning (DRL) for a number of years. Updating value functions with…

cs.LG2019

Flow-based Intrinsic Curiosity Module

Hsuan-Kung Yang, Po-Han Chiang, Min-Fong Hong +1

In this paper, we focus on a prediction-based novelty estimation strategy upon the deep reinforcement learning (DRL) framework, and present a flow-based intrinsic curiosity module…

cs.LG2019★ 9 cited

Never Forget: Balancing Exploration and Exploitation via Learning Optical Flow

Hsuan-Kung Yang, Po-Han Chiang, Kuan-Wei Ho +2

Exploration bonus derived from the novelty of the states in an environment has become a popular approach to motivate exploration for deep reinforcement learning agents in the past…

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