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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

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

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Editors: Joan Bruna, Jan Hesthaven, Lenka Zdeborova

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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

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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

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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

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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

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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

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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

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Spectral Geometric Matrix Completion

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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Dynamic Algorithms for Online Multiple Testing

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

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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

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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

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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

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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

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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

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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

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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

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