Zhanxing Zhu
40 papers · 2015–2026 · 8 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 17 separate collaboration groups - the largest holds only 23% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Zhanxing Zhu?
5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Dinghuai Zhang, Tianyuan Zhang, Yanzhi Chen
6 papers
· 2019–2021
· ICML, NeurIPS, ICLR
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Neural Approximate Sufficient Statistics for Implicit Models
ICLR 2021
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
NeurIPS 2020
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
ICML 2020
On Breaking Deep Generative Model-based Defenses and Beyond
ICML 2020
Interpreting Adversarially Trained Convolutional Neural Networks
ICML 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
NeurIPS 2019
12 papers whose co-authors appear nowhere else under this name
ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction
AAAI 2026
Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems
ICML 2025
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
NeurIPS 2024
MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows
ICML 2023
Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling
NeurIPS 2023
Implicit Bias of Adversarial Training for Deep Neural Networks
ICLR 2022
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
ICML 2021
Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting
AAAI 2021
Spherical Motion Dynamics: Learning Dynamics of Normalized Neural Network using SGD and Weight Decay
NeurIPS 2021
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
NeurIPS 2020
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
NeurIPS 2018
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
NeurIPS 2015