◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

P. Weng

4 papers here

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

author position
  • middle author2
  • last author2

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

fields
  • cs.LG2
  • cs.AI1
  • cs.RO1

identity via Semantic Scholar / OpenAlex

most citedLearning Symbolic Rules for Interpretable Deep Reinforcement Learning

8 citations · 16 across the 3 of their papers we have counts for

collaborators

4 papers

cs.AI2021★ 8 cited

Learning Symbolic Rules for Interpretable Deep Reinforcement Learning

Zhihao Ma, Yuzheng Zhuang, Paul Weng +4

Recent progress in deep reinforcement learning (DRL) can be largely attributed to the use of neural networks. However, this black-box approach fails to explain the learned policy i…

cs.LG2021★ 1 cited

Safe Distributional Reinforcement Learning

Jianyi Zhang, Paul Weng

Safety in reinforcement learning (RL) is a key property in both training and execution in many domains such as autonomous driving or finance. In this paper, we formalize it with a…

cs.LG2021★ 7 cited

Analytics and Machine Learning in Vehicle Routing Research

Ruibin Bai, Xinan Chen, Zhi-Long Chen +13

The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle…

cs.RO2020

Hyperparameter Auto-tuning in Self-Supervised Robotic Learning

Jiancong Huang, Juan Rojas, Matthieu Zimmer +3

Policy optimization in reinforcement learning requires the selection of numerous hyperparameters across different environments. Fixing them incorrectly may negatively impact optimi…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.