惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

U
Unit 42
P
Proofpoint News Feed
The Last Watchdog
The Last Watchdog
S
Secure Thoughts
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
N
News | PayPal Newsroom
Application and Cybersecurity Blog
Application and Cybersecurity Blog
O
OpenAI News
S
Security @ Cisco Blogs
宝玉的分享
宝玉的分享
Hacker News: Ask HN
Hacker News: Ask HN
T
Troy Hunt's Blog
Google Online Security Blog
Google Online Security Blog
WordPress大学
WordPress大学
有赞技术团队
有赞技术团队
TaoSecurity Blog
TaoSecurity Blog
Help Net Security
Help Net Security
Latest news
Latest news
NISL@THU
NISL@THU
S
Security Affairs
博客园_首页
C
CXSECURITY Database RSS Feed - CXSecurity.com
博客园 - 聂微东
AI
AI
www.infosecurity-magazine.com
www.infosecurity-magazine.com
Recent Announcements
Recent Announcements
P
Privacy & Cybersecurity Law Blog
小众软件
小众软件
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Hugging Face - Blog
Hugging Face - Blog
博客园 - 司徒正美
AWS News Blog
AWS News Blog
W
WeLiveSecurity
Google DeepMind News
Google DeepMind News
I
InfoQ
Schneier on Security
Schneier on Security
Recent Commits to openclaw:main
Recent Commits to openclaw:main
T
The Exploit Database - CXSecurity.com
IT之家
IT之家
T
Threatpost
Scott Helme
Scott Helme
L
LINUX DO - 热门话题
腾讯CDC
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
N
News and Events Feed by Topic
L
LINUX DO - 最新话题
F
Full Disclosure
大猫的无限游戏
大猫的无限游戏
H
Heimdal Security Blog
S
SegmentFault 最新的问题

Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

[edit]

Volume 145: Mathematical and Scientific Machine Learning, 16-19 August 2021, Virtual Conference

[edit]

Editors: Joan Bruna, Jan Hesthaven, Lenka Zdeborova

[bib][citeproc]

Filter Authors: Filter Titles:

Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data

; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1-36

[abs][Download PDF]

Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes

Andrea Agazzi, Jianfeng Lu; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:37-74

[abs][Download PDF]

BEAR: Sketching BFGS Algorithm for Ultra-High Dimensional Feature Selection in Sublinear Memory

Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, Ozan Koyluoglu, Kannan Ramchandran; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:75-92

[abs][Download PDF]

Multilevel Stein variational gradient descent with applications to Bayesian inverse problems

Terrence Alsup, Luca Venturi, Benjamin Peherstorfer; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:93-117

[abs][Download PDF]

Interpretable and Learnable Super-Resolution Time-Frequency Representation

Randall Balestriero, Herve Glotin, Richard Baranuik; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:118-152

[abs][Download PDF]

Average-Case Integrality Gap for Non-Negative Principal Component Analysis

Afonso Bandeira, Dmitriy Kunisky, Alexander Wein; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:153-171

[abs][Download PDF]

Spectral Geometric Matrix Completion

Amit Boyarski, Sanketh Vedula, Alex Bronstein; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:172-196

[abs][Download PDF]

Deep Autoencoders: From Understanding to Generalization Guarantees

Romain Cosentino, Randall Balestriero, Richard Baranuik, Behnaam Aazhang; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:197-222

[abs][Download PDF]

Numerical Calabi-Yau metrics from holomorphic networks

Michael Douglas, Subramanian Lakshminarasimhan, Yidi Qi; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:223-252

[abs][Download PDF]

Some observations on high-dimensional partial differential equations with Barron data

Weinan E, Stephan Wojtowytsch; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:253-269

[abs][Download PDF]

On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers

Weinan E, Stephan Wojtowytsch; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:270-290

[abs][Download PDF]

Reconstruction of Pairwise Interactions using Energy-Based Models

Christoph Feinauer, Carlo Lucibello; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:291-313

[abs][Download PDF]

Sharp threshold for alignment of graph databases with Gaussian weights

Luca Ganassali; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:314-335

[abs][Download PDF]

Deep Generative Learning via Euler Particle Transport

Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu, Xiliang Lu, Zhijian Yang; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:336-368

[abs][Download PDF]

Ground States of Quantum Many Body Lattice Models via Reinforcement Learning

Willem Gispen, Austen Lamacraft; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:369-385

[abs][Download PDF]

Solving Bayesian Inverse Problems via Variational Autoencoders

Hwan Goh, Sheroze Sheriffdeen, Jonathan Wittmer, Tan Bui-Thanh; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:386-425

[abs][Download PDF]

The Gaussian equivalence of generative models for learning with shallow neural networks

Sebastian Goldt, Bruno Loureiro, Galen Reeves, Florent Krzakala, Marc Mezard, Lenka Zdeborova; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:426-471

[abs][Download PDF]

Orientation-Preserving Vectorized Distance Between Curves

Jeff Phillips, Hasan Pourmahmood-Aghababa; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:472-496

[abs][Download PDF]

Adversarial Robustness of Stabilized Neural ODE Might be from Obfuscated Gradients

Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, Yuan Yao; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:497-515

[abs][Download PDF]

Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging

Hannah Lawrence, David Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrie; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:516-567

[abs][Download PDF]

A deep learning method for solving Fokker-Planck equations

Jiayu Zhai, Matthew Dobson, Yao Li; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:568-597

[abs][Download PDF]

A semigroup method for high dimensional committor functions based on neural network

Haoya Li, Yuehaw Khoo, Yinuo Ren, Lexing Ying; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:598-618

[abs][Download PDF]

Decentralized Multi-Agents by Imitation of a Centralized Controller

Alex Tong Lin, Mark Debord, Katia Estabridis, Gary Hewer, Guido Montufar, Stanley Osher; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:619-651

[abs][Download PDF]

A Data Driven Method for Computing Quasipotentials

Bo Lin, Qianxiao Li, Weiqing Ren; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:652-670

[abs][Download PDF]

A Qualitative Study of the Dynamic Behavior for Adaptive Gradient Algorithms

Chao Ma, Lei Wu, Weinan E; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:671-692

[abs][Download PDF]

Construction of optimal spectral methods in phase retrieval

Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborova; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:693-720

[abs][Download PDF]

Practical and Fast Momentum-Based Power Methods

Tahseen Rabbani, Apollo Jain, Arjun Rajkumar, Furong Huang; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:721-756

[abs][Download PDF]

Active Importance Sampling for Variational Objectives Dominated by Rare Events: Consequences for Optimization and Generalization

Grant M Rotskoff, Andrew R Mitchell, Eric Vanden-Eijnden; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:757-780

[abs][Download PDF]

Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh–Nagumo ODE

Johann Rudi, Julie Bessac, Amanda Lenzi; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:781-808

[abs][Download PDF]

Solvable Model for Inheriting the Regularization through Knowledge Distillation

Luca Saglietti, Lenka Zdeborova; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:809-846

[abs][Download PDF]

Reduced Order Modeling using Shallow ReLU Networks with Grassmann Layers

Kayla Bollinger, Hayden Schaeffer; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:847-867

[abs][Download PDF]

Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory?

Mariia Seleznova, Gitta Kutyniok; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:868-895

[abs][Download PDF]

Robust Certification for Laplace Learning on Geometric Graphs

Matthew Thorpe, Bao Wang; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:896-920

[abs][Download PDF]

Kernel-Based Smoothness Analysis of Residual Networks

Tom Tirer, Joan Bruna, Raja Giryes; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:921-954

[abs][Download PDF]

Dynamic Algorithms for Online Multiple Testing

Ziyu Xu, Aaditya Ramdas; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:955-986

[abs][Download PDF]

Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm

Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Hector D Ceniceros; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:987-1012

[abs][Download PDF]

Generalization and Memorization: The Bias Potential Model

Hongkang Yang, Weinan E; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1013-1043

[abs][Download PDF]

Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy Networks

Jiahao Yao, Paul Kottering, Hans Gundlach, Lin Lin, Marin Bukov; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1044-1081

[abs][Download PDF]

Implicit Form Neural Network for Learning Scalar Hyperbolic Conservation Laws

Xiaoping Zhang, Tao Cheng, Lili Ju; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1082-1098

[abs][Download PDF]

Borrowing From the Future: Addressing Double Sampling in Model-free Control

Yuhua Zhu, Zachary Izzo, Lexing Ying; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1099-1136

[abs][Download PDF]

Hessian-Aided Random Perturbation (HARP) Using Noisy Zeroth-Order Queries

Jingyi Zhu; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1137-1160

[abs][Download PDF]

Hessian Estimation via Stein’s Identity in Black-Box Problems

Jingyi Zhu; Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, PMLR 145:1161-1178

[abs][Download PDF]