Wenbing Huang

One Path to Model Them All: Learnable-Time Flow Matching for Crystal Structure and Energy Prediction

Crystals are cornerstone materials for semiconductors and renewable energy, yet their discovery is hindered by the prohibitive cost of Density Functional Theory (DFT). While geometric graph neural networks have advanced Crystal Structure Prediction (CSP) and energy estimation, existing methods treat these tasks as disp...