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2020 – today
- 2024
[c8]Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun, Chien Feng, Cho-Jui Hsieh, Chun-Yi Lee:
Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning. ICML 2024- [c7]Hsu-Shen Liu, So Kuroki, Tadashi Kozuno, Wei-Fang Sun, Chun-Yi Lee:
Language-Guided Pattern Formation for Swarm Robotics with Multi-Agent Reinforcement Learning. IROS 2024: 8998-9005 - [i9]Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun, Chien Feng, Cho-Jui Hsieh, Chun-Yi Lee:
Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning. CoRR abs/2402.01057 (2024) - [i8]Mu-Yi Shen, Chia-Chi Hsu, Hao-Yu Hou, Yu-Chen Huang, Wei-Fang Sun, Chia-Che Chang, Yu-Lun Liu, Chun-Yi Lee:
DriveEnv-NeRF: Exploration of A NeRF-Based Autonomous Driving Environment for Real-World Performance Validation. CoRR abs/2403.15791 (2024) - [i7]Chen-Hao Chao, Chien Feng, Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee:
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow. CoRR abs/2405.13629 (2024) - [i6]I-Chun Chen, Hsu-Shen Liu, Wei-Fang Sun, Chen-Hao Chao, Yen-Chang Hsu, Chun-Yi Lee:
Retraining-Free Merging of Sparse Mixture-of-Experts via Hierarchical Clustering. CoRR abs/2410.08589 (2024) - 2023
- [j3]Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee:
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning. J. Mach. Learn. Res. 24: 220:1-220:32 (2023) - [c6]Bo-Wun Cheng, En-Ming Huang
, Chen-Hao Chao, Wei-Fang Sun, Tsung Tai Yeh, Chun-Yi Lee:
COLAB: Collaborative and Efficient Processing of Replicated Cache Requests in GPU. ASP-DAC 2023: 314-319 - [c5]Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Chun-Yi Lee:
On Investigating the Conservative Property of Score-Based Generative Models. ICML 2023: 4076-4095 - [c4]Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee:
Training Energy-Based Normalizing Flow with Score-Matching Objectives. NeurIPS 2023 - [i5]Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee:
Training Energy-Based Normalizing Flow with Score-Matching Objectives. CoRR abs/2305.15267 (2023) - [i4]Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee:
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning. CoRR abs/2306.02430 (2023) - 2022
- [c3]Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee:
Denoising Likelihood Score Matching for Conditional Score-based Data Generation. ICLR 2022 - [i3]Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee:
Denoising Likelihood Score Matching for Conditional Score-based Data Generation. CoRR abs/2203.14206 (2022) - [i2]Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Chun-Yi Lee:
Quasi-Conservative Score-based Generative Models. CoRR abs/2209.12753 (2022) - 2021
- [j2]Wei-Fang Sun, Hung-Hsin Chen, ShaoFu Lin, YuanChing Lin, Jing-Wei Wu, En-Te Lin, Jerry Chou:
Critique of "Planetary Normal Mode Computation: Parallel Algorithms, Performance, and Reproducibility" by SCC Team From National Tsing Hua University. IEEE Trans. Parallel Distributed Syst. 32(11): 2623-2626 (2021) - [c2]Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee:
A Distributional Perspective on Value Function Factorization Methods for Multi-Agent Reinforcement Learning. AAMAS 2021: 1671-1673 - [c1]Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee:
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning. ICML 2021: 9945-9954 - [i1]Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee:
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning. CoRR abs/2102.07936 (2021) - 2020
- [j1]Wei-Fang Sun, Shih-Hsien Chan, Zhe-Ting Liu, Yu-Hung Yeh, Pai H. Chou:
Quatros: a preemptive multithreaded embedded OS for education. SIGBED Rev. 17(1): 49-55 (2020)
Coauthor Index
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