Paul Hand

According to our database, Paul Hand authored at least 38 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model.

Daniel Goldfarb, Itay Evron, Nir Weinberger, Daniel Soudry, Paul Hand

CoRR, 2024

2023

Regularized Training of Intermediate Layers for Generative Models for Inverse Problems.

Sean Gunn, Jorio Cocola, Paul Hand

Trans. Mach. Learn. Res., 2023

Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime.

Daniel Goldfarb, Paul Hand

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Theoretical Perspectives on Deep Learning Methods in Inverse Problems.

Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar

IEEE J. Sel. Areas Inf. Theory, September, 2022

Guest Editorial.

Paul Hand, Reinhard Heckel, Jonathan Scarlett

IEEE J. Sel. Areas Inf. Theory, September, 2022

2021

No Statistical-Computational Gap in Spiked Matrix Models with Generative Network Priors.

Jorio Cocola, Paul Hand, Vladislav Voroninski

Entropy, 2021

Score-based Generative Neural Networks for Large-Scale Optimal Transport.

Max Daniels, Tyler Maunu, Paul Hand

CoRR, 2021

Generator Surgery for Compressed Sensing.

Niklas Smedemark-Margulies, Jung Yeon Park, Max Daniels, Rose Yu, Jan-Willem van de Meent, Paul Hand

CoRR, 2021

Score-based Generative Neural Networks for Large-Scale Optimal Transport.

Grady Daniels, Tyler Maunu, Paul Hand

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Bilinear Compressed Sensing Under Known Signs via Convex Programming.

Alireza Aghasi, Ali Ahmed, Paul Hand, Babhru Joshi

IEEE Trans. Signal Process., 2020

Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk.

Paul Hand, Vladislav Voroninski

IEEE Trans. Inf. Theory, 2020

Optimal Sample Complexity of Gradient Descent for Amplitude Flow via Non-Lipschitz Matrix Concentration.

Paul Hand, Oscar Leong, Vladislav Voroninski

CoRR, 2020

Compressive Phase Retrieval: Optimal Sample Complexity with Deep Generative Priors.

Paul Hand, Oscar Leong, Vladislav Voroninski

CoRR, 2020

Nonasymptotic Guarantees for Low-Rank Matrix Recovery with Generative Priors.

Jorio Cocola, Paul Hand, Vladislav Voroninski

CoRR, 2020

Global Convergence of Sobolev Training for Overparametrized Neural Networks.

Jorio Cocola, Paul Hand

CoRR, 2020

Reducing the Representation Error of GAN Image Priors Using the Deep Decoder.

Max Daniels, Paul Hand, Reinhard Heckel

CoRR, 2020

Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors.

Jorio Cocola, Paul Hand, Vladislav Voroninski

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Global Convergence of Sobolev Training for Overparameterized Neural Networks.

Jorio Cocola, Paul Hand

Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Invertible generative models for inverse problems: mitigating representation error and dataset bias.

Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Simultaneous Phase Retrieval and Blind Deconvolution via Convex Programming.

Ali Ahmed, Alireza Aghasi, Paul Hand

J. Mach. Learn. Res., 2019

Invertible generative models for inverse problems: mitigating representation error and dataset bias.

Muhammad Asim, Ali Ahmed, Paul Hand

CoRR, 2019

Global Guarantees for Blind Demodulation with Generative Priors.

Paul Hand, Babhru Joshi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks.

Reinhard Heckel, Paul Hand

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

ROPTLIB: An Object-Oriented C++ Library for Optimization on Riemannian Manifolds.

Wen Huang, Pierre-Antoine Absil, Kyle A. Gallivan, Paul Hand

ACM Trans. Math. Softw., 2018

Blind Deconvolution by a Steepest Descent Algorithm on a Quotient Manifold.

Wen Huang, Paul Hand

SIAM J. Imaging Sci., 2018

Exact Simultaneous Recovery of Locations and Structure from Known Orientations and Corrupted Point Correspondences.

Paul Hand, Choongbum Lee, Vladislav Voroninski

Discret. Comput. Geom., 2018

Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior.

Reinhard Heckel, Wen Huang, Paul Hand, Vladislav Voroninski

CoRR, 2018

Phase Retrieval Under a Generative Prior.

Paul Hand, Oscar Leong, Vladislav Voroninski

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Blind Deconvolutional Phase Retrieval via Convex Programming.

Ali Ahmed, Alireza Aghasi, Paul Hand

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A convex program for bilinear inversion of sparse vectors.

Alireza Aghasi, Ali Ahmed, Paul Hand, Babhru Joshi

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

BranchHull: Convex bilinear inversion from the entrywise product of signals with known signs.

Alireza Aghasi, Ali Ahmed, Paul Hand

CoRR, 2017

Convex inversion of the entrywise product of real signals with known signs.

Alireza Aghasi, Ali Ahmed, Paul Hand

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Corruption Robust Phase Retrieval via Linear Programming.

Paul Hand, Vladislav Voroninski

CoRR, 2016

Compressed Sensing from Phaseless Gaussian Measurements via Linear Programming in the Natural Parameter Space.

Paul Hand, Vladislav Voroninski

CoRR, 2016

An Elementary Proof of Convex Phase Retrieval in the Natural Parameter Space via the Linear Program PhaseMax.

Paul Hand, Vladislav Voroninski

CoRR, 2016

ShapeFit and ShapeKick for Robust, Scalable Structure from Motion.

Thomas A. Goldstein, Paul Hand, Choongbum Lee, Vladislav Voroninski, Stefano Soatto

Proceedings of the Computer Vision - ECCV 2016, 2016

Robust phaselift for phase retrieval under corruptions.

Paul Hand, Thang Huynh

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

ShapeFit: Exact location recovery from corrupted pairwise directions.

Paul Hand, Choongbum Lee, Vladislav Voroninski

CoRR, 2015