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 Bing Yu, Ke Sun, Zhouchen Lin
9 papers
· 2018–2023
· ACML, AAAI, ICML
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Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy
ACML 2023
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
ICLR 2021
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes
AAAI 2020
On the Noisy Gradient Descent that Generalizes as SGD
ICML 2020
Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks
ACML 2020
SpHMC: Spectral Hamiltonian Monte Carlo
AAAI 2019
Tangent-Normal Adversarial Regularization for Semi-Supervised Learning
CVPR 2019
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
ICML 2019
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
IJCAI 2018
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