19 papers
Fast Organic Crystal Structure Prediction with Unit Cell Flow Matching
Alston Lo, Luka Mucko, Austin H. Cheng +4
Organic crystal structure prediction (CSP) is a requirement for computational modelling of organic solids, but traditionally costs several CPU-years per molecule. Generative models…
SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization
Jamison Meindl, Yunsheng Tian, Tony Cui +5
Optimizing an experimental system can be extremely challenging when each experiment is expensive, time-consuming, or difficult to perform. Existing optimizers for expensive black-b…
Hierarchical Transformer Preconditioning for Interactive Physics Simulation
Carl Osborne, Minghao Guo, Crystal Owens +1
Neural preconditioners for real-time physics simulation offer promising data-driven priors, but they often fail to capture long-range couplings efficiently because they inherit loc…
Neural Statistical Functions
Daniel Xu, Yuxin Xie, Minghao Guo +2
Classical deep learning typically operates on individual cases. Despite its success, real-world usage often requires repeated inference to estimate statistical quantities for compl…
RigidFormer: Learning Rigid Dynamics using Transformers
Zhiyang Dou, Minghao Guo, Haixu Wu +3
Learning-based simulation of multi-object rigid-body dynamics remains difficult because contact is discontinuous and errors compound over long horizons. Most existing methods remai…
Kinematic Kitbashing
Minghao Guo, Victor Zordan, Sheldon Andrews +3
We introduce Kinematic Kitbashing, an optimization framework that synthesizes articulated 3D objects by assembling reusable parts conditioned on an abstract kinematic graph. Given…