3 citations · 13 across the 23 of their papers we have counts for
28 papers
On Meeks' conjecture on disjoint minimal graphs
Angelo Benedetti, Barbara Nelli
We study disjoint solution pairs to the minimal surface equation in , with on A conjecture of W. Meeks states that at most two such pairs…
Scientific Discovery under Validation Congestion via Multi-Fidelity Pairwise Rankings
Kevin Tirta Wijaya, Alston Lo, Michael Sun +2
Modern computational methods can now propose candidate molecules, materials, and other scientific designs at an unprecedented scale, creating a validation congestion where candidat…
From Surfaces to Volumes: Registered Geometry for Protein Representation Learning
Siyuan Chen, Cai Zhou, Jinrui Zhang +8
Existing protein geometry models typically represent molecular surfaces using local geometric features such as sampled points, normals, and curvature. While effective for capturing…
Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation
Jiaben Chen, Sixun Dong, Qinhong Zhou +4
Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both visual identity and character behavior-requirements that remain diffic…
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…
A Neural Hierarchical-Matrix Preconditioner for Real-Time GPU Solves
Carl Osborne, Minghao Guo, Crystal Owens +1
Interactive simulation solves Ax=b for a sparse SPD A that changes every frame, inside an 8-16 ms budget. At a few thousand unknowns, the setup of algebraic multigrid alone exceeds…
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…
PhyScensis: Physics-Augmented LLM Agents for Complex Physical Scene Arrangement
Yian Wang, Han Yang, Minghao Guo +5
Automatically generating interactive 3D environments is crucial for scaling up robotic data collection in simulation. While prior work has primarily focused on 3D asset placement,…
Protein Structure Tokenization via Geometric Byte Pair Encoding
Michael Sun, Weize Yuan, Gang Liu +2
Protein structure is central to biological function, and enabling multimodal protein models requires joint reasoning over sequence, structure, and function. A key barrier is the la…
ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization
Jamison Meindl, Yunsheng Tian, Tony Cui +6
Global optimization of expensive, derivative-free black-box functions requires extreme sample efficiency. While Bayesian optimization (BO) is the current state-of-the-art, its perf…
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…
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…
Physically Valid Biomolecular Interaction Modeling with Gauss-Seidel Projection
Siyuan Chen, Minghao Guo, Caoliwen Wang +6
Biomolecular interaction modeling has been substantially advanced by foundation models, yet they often produce all-atom structures that violate basic steric feasibility. We address…
Post Hoc Regression Refinement via Pairwise Rankings
Kevin Tirta Wijaya, Michael Sun, Minghao Guo +3
Accurate prediction of continuous properties is essential to many scientific and engineering tasks. Although deep-learning regressors excel with abundant labels, their accuracy det…
A Genetic Algorithm for Navigating Synthesizable Molecular Spaces
Alston Lo, Connor W. Coley, Wojciech Matusik
Inspired by the effectiveness of genetic algorithms and the importance of synthesizability in molecular design, we present SynGA, a simple genetic algorithm that operates directly…
Directed Graph Grammars for Sequence-based Learning
Michael Sun, Orion Foo, Gang Liu +2
Directed acyclic graphs (DAGs) are a class of graphs commonly used in practice, with examples that include electronic circuits, Bayesian networks, and neural architectures. While m…
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages
Michael Sun, Weize Yuan, Gang Liu +2
Recent data-efficient molecular generation approaches exploit graph grammars to introduce interpretability into the generative models. However, grammar learning therein relies on e…
FlashBias: Fast Computation of Attention with Bias
Haixu Wu, Minghao Guo, Yuezhou Ma +4
Attention with bias, which extends standard attention by introducing prior knowledge as an additive bias matrix to the query-key scores, has been widely deployed in vision, languag…
Two-Stage Pretraining for Molecular Property Prediction in the Wild
Kevin Tirta Wijaya, Minghao Guo, Michael Sun +3
Molecular deep learning models have achieved remarkable success in property prediction, but they often require large amounts of labeled data. The challenge is that, in real-world a…
Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
Gang Liu, Michael Sun, Wojciech Matusik +2
While large language models (LLMs) have integrated images, adapting them to graphs remains challenging, limiting their applications in materials and drug design. This difficulty st…
Procedural Synthesis of Synthesizable Molecules
Michael Sun, Alston Lo, Minghao Guo +3
Designing synthetically accessible molecules and recommending analogs to unsynthesizable molecules are important problems for accelerating molecular discovery. We reconceptualize b…
Physically Compatible 3D Object Modeling from a Single Image
Minghao Guo, Bohan Wang, Pingchuan Ma +6
We present a computational framework that transforms single images into 3D physical objects. The visual geometry of a physical object in an image is determined by three orthogonal…
TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes
Minghao Guo, Bohan Wang, Kaiming He +1
We introduce TetSphere Splatting, a Lagrangian geometry representation designed for high-quality 3D shape modeling. TetSphere splatting leverages an underused yet powerful geometri…