Jiaoyang Huang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 29

Top Topics

Affine Invariance

Top Venues

Publications

José A. Carrillo, Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Dongyi Wei
Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities. CoRR (2024)
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows. CoRR (2024)
Gérard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath
High-dimensional SGD aligns with emerging outlier eigenspaces. ICLR (2024)
Daniel Zhengyu Huang, Jiaoyang Huang, Zhengjiang Lin
Convergence Analysis of Probability Flow ODE for Score-based Generative Models. CoRR (2024)
Gérard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath
High-dimensional SGD aligns with emerging outlier eigenspaces. CoRR (2023)
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Sampling via Gradient Flows in the Space of Probability Measures. CoRR (2023)
Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang
How Does Information Bottleneck Help Deep Learning? ICML (2023)
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance. CoRR (2023)
Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang
How Does Information Bottleneck Help Deep Learning? CoRR (2023)
Han Gao, Xu Han, Jiaoyang Huang, Jian-Xun Wang, Li-Ping Liu
PatchGT: Transformer over Non-trainable Clusters for Learning Graph Representations. CoRR (2022)
Jiaoyang Huang, Daniel Zhengyu Huang, Qing Yang, Guang Cheng
Power Iteration for Tensor PCA. J. Mach. Learn. Res. 23 (2022)
Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang
Robustness Implies Generalization via Data-Dependent Generalization Bounds. ICML (2022)
Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Efficient Derivative-free Bayesian Inference for Large-Scale Inverse Problems. CoRR (2022)
Han Gao, Xu Han, Jiaoyang Huang, Jian-Xun Wang, Liping Liu
PatchGT: Transformer Over Non-Trainable Clusters for Learning Graph Representations. LoG (2022)
Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang
Robustness Implies Generalization via Data-Dependent Generalization Bounds. CoRR (2022)
Gérard Ben Arous, Daniel Zhengyu Huang, Jiaoyang Huang
Long Random Matrices and Tensor Unfolding. CoRR (2021)
Daniel Zhengyu Huang, Jiaoyang Huang
Improve Unscented Kalman Inversion With Low-Rank Approximation and Reduced-Order Model. CoRR (2021)
Daniel Zhengyu Huang, Jiaoyang Huang
Unscented Kalman Inversion: Efficient Gaussian Approximation to the Posterior Distribution. CoRR (2021)
Clement Gehring, Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization. NeurIPS (2021)
Zhun Deng, Jiaoyang Huang, Kenji Kawaguchi
How Shrinking Gradient Noise Helps the Performance of Neural Networks. IEEE BigData (2021)
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su
Towards Understanding the Dynamics of the First-Order Adversaries. ICML (2020)
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su
Towards Understanding the Dynamics of the First-Order Adversaries. CoRR (2020)
Jiaoyang Huang, Horng-Tzer Yau
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy. ICML (2020)
Kenji Kawaguchi, Jiaoyang Huang
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes. CoRR (2019)
Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling
Effect of Depth and Width on Local Minima in Deep Learning. Neural Comput. 31 (7) (2019)
Jiaoyang Huang, Horng-Tzer Yau
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy. CoRR (2019)
Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling
Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning. Neural Comput. 31 (12) (2019)
Kenji Kawaguchi, Jiaoyang Huang
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes. Allerton (2019)
Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling
Effect of Depth and Width on Local Minima in Deep Learning. CoRR (2018)