Zhi-ming Ma

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control ICML 2025 Improved Diffusion-based Generative Model with Better Adversarial Robustness ICLR 2025 UniGEM: A Unified Approach to Generation and Property Prediction for Molecules ICLR 2025 Wavelet Diffusion Neural Operator ICLR 2025 Better Neural PDE Solvers Through Data-Free Mesh Movers ICLR 2024 DiffPhyCon: A Generative Approach to Control Complex Physical Systems NeurIPS 2024 Neural Jump-Diffusion Temporal Point Processes ICML 2024 Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion ICML 2024 Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment ICLR 2024 Sliced Denoising: A Physics-Informed Molecular Pre-Training Method ICLR 2024 The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling ICML 2024 UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning ICML 2024 A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining ICML 2023 A new perspective on building efficient and expressive 3D equivariant graph neural networks NeurIPS 2023 Breaking Correlation Shift via Conditional Invariant Regularizer ICLR 2023 Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization ICML 2023 Fractional Denoising for 3D Molecular Pre-training ICML 2023 Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion NeurIPS 2023 SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models NeurIPS 2023 Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials NeurIPS 2023 Characterization of Excess Risk for Locally Strongly Convex Population Risk NeurIPS 2022 Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS 2022 Gradient Information Matters in Policy Optimization by Back-propagating through Model ICLR 2022 When Does Group Invariant Learning Survive Spurious Correlations? NeurIPS 2022 Reweighting Augmented Samples by Minimizing the Maximal Expected Loss ICLR 2021 Uncertainty Calibration for Ensemble-Based Debiasing Methods NeurIPS 2021 BN-invariant Sharpness Regularizes the Training Model to Better Generalization IJCAI 2019 G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space ICLR 2019 Differential Equations for Modeling Asynchronous Algorithms IJCAI 2018 Asynchronous Stochastic Gradient Descent with Delay Compensation ICML 2017 Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting NeurIPS 2017 A Communication-Efficient Parallel Algorithm for Decision Tree NeurIPS 2016 Asynchronous Accelerated Stochastic Gradient Descent IJCAI 2016 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010 Ranking Measures and Loss Functions in Learning to Rank NeurIPS 2009