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

Ben Adcock, Simone Brugiapaglia, Nick Dexter, Sebastian Morage; 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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