activity
20232026
most citedAERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

PC-Diffuser: Path-Consistent Capsule CBF Safety Filtering for Diffusion-Based Trajectory Planner

Eugene Ku, Yiwei Lyu

Autonomous driving in complex traffic requires planners that generalize beyond hand-crafted rules, motivating data-driven approaches that learn behavior from expert demonstrations.…

cs.LG20251 cited

AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions

Väinö Hatanpää, Eugene Ku, Jason Stock +12

Generative machine learning offers new opportunities to better understand complex Earth system dynamics. Recent diffusion-based methods address spectral biases and improve ensemble…

hep-ex2024

Real-time Position Reconstruction for the KamLAND-Zen Experiment using Hardware-AI Co-design

Alexander Migala, Eugene Ku, Zepeng Li +1

Monolithic liquid scintillator detector technology is the workhorse for detecting neutrinos and exploring new physics. The KamLAND-Zen experiment exemplifies this detector technolo…

cs.LG2024

FlyKD: Graph Knowledge Distillation on the Fly with Curriculum Learning

Eugene Ku

Knowledge Distillation (KD) aims to transfer a more capable teacher model's knowledge to a lighter student model in order to improve the efficiency of the model, making it faster a…

cs.LG2023

Stronger Graph Transformer with Regularized Attention Scores

Eugene Ku

Graph Neural Networks are notorious for its memory consumption. A recent Transformer-based GNN called Graph Transformer is shown to obtain superior performances when long range dep…