Zhi-ming Ma
35 papers · 2009–2025 · 4 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+12 more ↓ Show less ↑
π§ Keyword Pioneer π Conference Polyglot (4) πΊοΈ Taxonomy Completionist (13) π Interdisciplinary Bridge π Academic Marathon (16)
π
Cross-Pollinator
(10)
πΊοΈ
Taxonomy Completionist
(13)
π§
Keyword Pioneer
π€
Dynamic Duo
(11)
π
Keyword Champion
π
Triple Crown
ποΈ
Keyword Collector
(114)
β
The Questioner
(2)
β‘
Prolific Year
(8)
π
Trend Setter
π
Century Club
(35)
π₯
Unstoppable
(5)
Conferences
NIPS (13)
ICLR (10)
ICML (9)
IJCAI (3)
Top co-authors
Keywords
generalization bound
(3)
stochastic differential equation
(3)
out-of-distribution generalization
(2)
molecule representation
(2)
geometric deep learning
(2)
domain generalization
(2)
diffusion model
(2)
learning to rank
(2)
drug discovery
(2)
asynchronous stochastic gradient descent
(2)
loss function
(2)
geometric representation
(2)
information retrieval
(1)
batch normalization
(1)
image generation
(1)
natural language inference
(1)
self-supervised learning
(1)
policy evaluation
(1)
representation learning
(1)
model calibration
(1)
Papers
Wavelet Diffusion Neural Operator
ICLR 2025
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
ICML 2025
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules
ICLR 2025
Improved Diffusion-based Generative Model with Better Adversarial Robustness
ICLR 2025
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
ICML 2024
Neural Jump-Diffusion Temporal Point Processes
ICML 2024
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
ICML 2024
DiffPhyCon: A Generative Approach to Control Complex Physical Systems
NIPS 2024
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
ICML 2024
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
ICLR 2024
Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment
ICLR 2024
Better Neural PDE Solvers Through Data-Free Mesh Movers
ICLR 2024
Fractional Denoising for 3D Molecular Pre-training
ICML 2023
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion
NIPS 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials
NIPS 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks
NIPS 2023
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
NIPS 2023
Breaking Correlation Shift via Conditional Invariant Regularizer
ICLR 2023
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization
ICML 2023
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
ICML 2023
Does Momentum Change the Implicit Regularization on Separable Data?
NIPS 2022
Characterization of Excess Risk for Locally Strongly Convex Population Risk
NIPS 2022
When Does Group Invariant Learning Survive Spurious Correlations?
NIPS 2022
Gradient Information Matters in Policy Optimization by Back-propagating through Model
ICLR 2022
Uncertainty Calibration for Ensemble-Based Debiasing Methods
NIPS 2021
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
ICLR 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
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting
NIPS 2017
Asynchronous Stochastic Gradient Descent with Delay Compensation
ICML 2017
A Communication-Efficient Parallel Algorithm for Decision Tree
NIPS 2016
Asynchronous Accelerated Stochastic Gradient Descent
IJCAI 2016
Two-Layer Generalization Analysis for Ranking Using Rademacher Average
NIPS 2010
Ranking Measures and Loss Functions in Learning to Rank
NIPS 2009