3 citations · 11 across the 16 of their papers we have counts for
4 papers · 1 filter
EUGens: Efficient, Unified, and General Dense Layers
Sang Min Kim, Byeongchan Kim, Arijit Sehanobish +7
Efficient neural networks are essential for scaling machine learning models to real-time applications and resource-constrained environments. Fully-connected feedforward layers (FFL…
Periodic Skill Discovery
Jonghae Park, Daesol Cho, Jusuk Lee +3
Unsupervised skill discovery in reinforcement learning (RL) aims to learn diverse behaviors without relying on external rewards. However, current methods often overlook the periodi…
SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning
Dongseok Shim, Seungjae Lee, H. Jin Kim
As previous representations for reinforcement learning cannot effectively incorporate a human-intuitive understanding of the 3D environment, they usually suffer from sub-optimal pe…
S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning
Daesol Cho, Dongseok Shim, H. Jin Kim
Offline reinforcement learning (Offline RL) suffers from the innate distributional shift as it cannot interact with the physical environment during training. To alleviate such limi…