1 citations · 1 across the 4 of their papers we have counts for
4 papers
PackFlow: Generative Molecular Crystal Structure Prediction via Reinforcement Learning Alignment
Akshay Subramanian, Elton Pan, Juno Nam +6
Organic molecular crystals underpin technologies ranging from pharmaceuticals to organic electronics, yet predicting solid-state packing of molecules remains challenging because ca…
Patch-aware Vector Quantized Codebook Learning for Unsupervised Visual Defect Detection
Qisen Cheng, Shuhui Qu, Janghwan Lee
Unsupervised visual defect detection is critical in industrial applications, requiring a representation space that captures normal data features while detecting deviations. Achievi…
Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching
Akshay Subramanian, Shuhui Qu, Cheol Woo Park +3
Amorphous molecular solids offer a promising alternative to inorganic semiconductors, owing to their mechanical flexibility and solution processability. The packing structure of th…
SHAPNN: Shapley Value Regularized Tabular Neural Network
Qisen Cheng, Shuhui Qu, Janghwan Lee
We present SHAPNN, a novel deep tabular data modeling architecture designed for supervised learning. Our approach leverages Shapley values, a well-established technique for explain…