Working Locally Thinking Globally - Part I: Theoretical Guarantees for Convolutional Sparse Coding. - Vardan Papyan; Jeremias Sulam; Michael Elad (CoRR, 2016)

Working Locally Thinking Globally - Part II: Stability and Algorithms for Convolutional Sparse Coding. - Vardan Papyan; Jeremias Sulam; Michael Elad (CoRR, 2016)

Multi-Scale Patch-Based Image Restoration. - Vardan Papyan; Michael Elad (IEEE Trans. Image Process., 2016)

Convolutional Dictionary Learning via Local Processing. - Vardan Papyan; Yaniv Romano; Michael Elad; Jeremias Sulam (ICCV, 2017)

Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. - Jeremias Sulam; Vardan Papyan; Yaniv Romano; Michael Elad (CoRR, 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)

Convolutional Neural Networks Analyzed via Convolutional Sparse Coding. - Vardan Papyan; Yaniv Romano; Michael Elad (J. Mach. Learn. Res., 2017)

Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding. - Vardan Papyan; Jeremias Sulam; Michael Elad (IEEE Trans. Signal Process., 2017)

Global Versus Local Modeling of Signals. - Vardan Papyan (2017)

Projecting on to the Multi-Layer Convolutional Sparse Coding Model. - Jeremias Sulam; Vardan Papyan; Yaniv Romano; Michael Elad (ICASSP, 2018)

Neural Proximal Gradient Descent for Compressive Imaging. - Morteza Mardani; Qingyun Sun; David L. Donoho; Vardan Papyan; Hatef Monajemi; Shreyas Vasanawala; John M. Pauly (NeurIPS, 2018)

The Full Spectrum of Deep Net Hessians At Scale: Dynamics with Sample Size. - Vardan Papyan (CoRR, 2018)

Multimodal latent variable analysis. - Vardan Papyan; Ronen Talmon (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)

Multilayer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. - Jeremias Sulam; Vardan Papyan; Yaniv Romano; Michael Elad (IEEE Trans. Signal Process., 2018)

Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians. - Vardan Papyan (ICML, 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)

Prevalence of Neural Collapse during the terminal phase of deep learning training. - Vardan Papyan; X. Y. Han; David L. Donoho (CoRR, 2020)

Traces of Class/Cross-Class Structure Pervade Deep Learning Spectra. - Vardan Papyan (CoRR, 2020)

Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path. - X. Y. Han; Vardan Papyan; David L. Donoho (ICLR, 2022)

Residual Alignment: Uncovering the Mechanisms of Residual Networks. - Jianing Li; Vardan Papyan (NeurIPS, 2023)

LLM Censorship: A Machine Learning Challenge or a Computer Security Problem? - David Glukhov; Ilia Shumailov; Yarin Gal; Nicolas Papernot; Vardan Papyan (CoRR, 2023)

Pushing Boundaries: Mixup's Influence on Neural Collapse. - Quinn LeBlanc Fisher; Haoming Meng; Vardan Papyan (ICLR, 2024)

Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift. - Benjamin Eyre; Elliot Creager; David Madras; Vardan Papyan; Richard S. Zemel (ICML, 2024)

Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches. - David Glukhov; Ilia Shumailov; Yarin Gal; Nicolas Papernot; Vardan Papyan (ICML, 2024)

Sparsest Models Elude Pruning: An Exposé of Pruning's Current Capabilities. - Stephen Zhang; Vardan Papyan (ICML, 2024)

Linguistic Collapse: Neural Collapse in (Large) Language Models. - Robert Wu; Vardan Papyan (NeurIPS, 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)

Transformer Alignment in Large Language Models. - Murdock Aubry; Haoming Meng; Anton Sugolov; Vardan Papyan (CoRR, 2024)

Transformer Block Coupling and its Correlation with Generalization in LLMs. - Murdock Aubry; Haoming Meng; Anton Sugolov; Vardan Papyan (ICLR, 2025)

Breach By A Thousand Leaks: Unsafe Information Leakage in 'Safe' AI Responses. - David Glukhov; Ziwen Han; Ilia Shumailov; Vardan Papyan; Nicolas Papernot (ICLR, 2025)

OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition. - Stephen Zhang; Vardan Papyan (ICLR, 2025)

Attention Sinks and Outlier Features: A 'Catch, Tag, and Release' Mechanism for Embeddings. - Stephen Zhang; Mustafa Khan; Vardan Papyan (CoRR, 2025)

On the Importance of Gaussianizing Representations. - Daniel Eftekhari; Vardan Papyan (CoRR, 2025)