3 papers
cs.LG2024
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
Chen-Hao Chao, Chien Feng, Wei-Fang Sun +3
Existing Maximum-Entropy (MaxEnt) Reinforcement Learning (RL) methods for continuous action spaces are typically formulated based on actor-critic frameworks and optimized through a…
cs.LG2024
Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning
Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun +3
In this paper, we focus on single-demonstration imitation learning (IL), a practical approach for real-world applications where acquiring multiple expert demonstrations is costly o…
cs.CV2024
Boosting Flow-based Generative Super-Resolution Models via Learned Prior
Li-Yuan Tsao, Yi-Chen Lo, Chia-Che Chang +4
Flow-based super-resolution (SR) models have demonstrated astonishing capabilities in generating high-quality images. However, these methods encounter several challenges during ima…