Vardan Papyan

According to our database, Vardan Papyan authored at least 30 papers between 2016 and 2024.

Collaborative distances:

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

2024

OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition.

Stephen Zhang, Vardan Papyan

CoRR, 2024

Transformer Alignment in Large Language Models.

Murdock Aubry, Haoming Meng, Anton Sugolov, Vardan Papyan

CoRR, 2024

A False Sense of Safety: Unsafe Information Leakage in 'Safe' AI Responses.

David Glukhov, Ziwen Han, Ilia Shumailov, Vardan Papyan, Nicolas Papernot

CoRR, 2024

Linguistic Collapse: Neural Collapse in (Large) Language Models.

Robert Wu, Vardan Papyan

CoRR, 2024

Sparsest Models Elude Pruning: An Exposé of Pruning's Current Capabilities.

Stephen Zhang, Vardan Papyan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches.

David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift.

Benjamin Eyre, Elliot Creager, David Madras, Vardan Papyan, Richard S. Zemel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Pushing Boundaries: Mixup's Influence on Neural Collapse.

Quinn LeBlanc Fisher, Haoming Meng, Vardan Papyan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?

David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan

CoRR, 2023

Residual Alignment: Uncovering the Mechanisms of Residual Networks.

Jianing Li, Vardan Papyan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path.

X. Y. Han, Vardan Papyan, David L. Donoho

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Traces of Class/Cross-Class Structure Pervade Deep Learning Spectra.

Vardan Papyan

CoRR, 2020

Prevalence of Neural Collapse during the terminal phase of deep learning training.

Vardan Papyan, X. Y. Han, David L. Donoho

CoRR, 2020

2019

Degrees of Freedom Analysis of Unrolled Neural Networks.

Morteza Mardani, Qingyun Sun, Vardan Papyan, Shreyas Vasanawala, John M. Pauly, David L. Donoho

CoRR, 2019

Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians.

Vardan Papyan

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Multilayer Convolutional Sparse Modeling: Pursuit and Dictionary Learning.

Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad

IEEE Trans. Signal Process., 2018

Theoretical Foundations of Deep Learning via Sparse Representations: A Multilayer Sparse Model and Its Connection to Convolutional Neural Networks.

Vardan Papyan, Yaniv Romano, Jeremias Sulam, Michael Elad

IEEE Signal Process. Mag., 2018

Multimodal latent variable analysis.

Vardan Papyan, Ronen Talmon

Signal Process., 2018

The Full Spectrum of Deep Net Hessians At Scale: Dynamics with Sample Size.

Vardan Papyan

CoRR, 2018

Neural Proximal Gradient Descent for Compressive Imaging.

Morteza Mardani, Qingyun Sun, David L. Donoho, Vardan Papyan, Hatef Monajemi, Shreyas Vasanawala, John M. Pauly

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

Projecting on to the Multi-Layer Convolutional Sparse Coding Model.

Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Global Versus Local Modeling of Signals.

Vardan Papyan

PhD thesis, 2017

Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding.

Vardan Papyan, Jeremias Sulam, Michael Elad

IEEE Trans. Signal Process., 2017

Convolutional Neural Networks Analyzed via Convolutional Sparse Coding.

Vardan Papyan, Yaniv Romano, Michael Elad

J. Mach. Learn. Res., 2017

Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery.

Morteza Mardani, Hatef Monajemi, Vardan Papyan, Shreyas Vasanawala, David L. Donoho, John M. Pauly

CoRR, 2017

Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning.

Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad

CoRR, 2017

Convolutional Dictionary Learning via Local Processing.

Vardan Papyan, Yaniv Romano, Michael Elad, Jeremias Sulam

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Multi-Scale Patch-Based Image Restoration.

Vardan Papyan, Michael Elad

IEEE Trans. Image Process., 2016

Working Locally Thinking Globally - Part II: Stability and Algorithms for Convolutional Sparse Coding.

Vardan Papyan, Jeremias Sulam, Michael Elad

CoRR, 2016

Working Locally Thinking Globally - Part I: Theoretical Guarantees for Convolutional Sparse Coding.

Vardan Papyan, Jeremias Sulam, Michael Elad

CoRR, 2016