Best basis selection using sparsity driven multi-family wavelet transform. - Romain Cosentino; Randall Balestriero; Behnaam Aazhang (GlobalSIP, 2016)

Overcomplete Frame Thresholding for Acoustic Scene Analysis. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Ankit B. Patel (CoRR, 2017)

Spline Filters For End-to-End Deep Learning. - Randall Balestriero; Romain Cosentino; Hervé Glotin; Richard G. Baraniuk (ICML, 2018)

The Geometry of Deep Networks: Power Diagram Subdivision. - Randall Balestriero; Romain Cosentino; Behnaam Aazhang; Richard G. Baraniuk (NeurIPS, 2019)

Learnable Group Transform For Time-Series. - Romain Cosentino; Behnaam Aazhang (ICML, 2020)

Provable Finite Data Generalization with Group Autoencoder. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Behnaam Aazhang (CoRR, 2020)

Sparse Multi-Family Deep Scattering Network. - Romain Cosentino; Randall Balestriero (CoRR, 2020)

Interpretable Image Clustering via Diffeomorphism-Aware K-Means. - Romain Cosentino; Randall Balestriero; Yanis Bahroun; Anirvan M. Sengupta; Richard G. Baraniuk; Behnaam Aazhang (CoRR, 2020)

Universal Frame Thresholding. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Behnaam Aazhang (IEEE Signal Process. Lett., 2020)

Graph-Based Interpolation of Local Activation Time on the Cardiac Surface. - Jennifer Hellar; Romain Cosentino; Mathews M. John; Allison Post; Skylar Buchan; Mehdi Razavi; Behnaam Aazhang (ACSCC, 2021)

Deep Autoencoders: From Understanding to Generalization Guarantees. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Behnaam Aazhang (MSML, 2021)

A novel convolutional neural network for reconstructing surface electrocardiograms from intracardiac electrograms and vice versa. - Anton Banta; Romain Cosentino; Mathews John; Allison Post; Skylar Buchan; Mehdi Razavi; Behnaam Aazhang (Artif. Intell. Medicine, 2021)

Spatial Transformer K-Means. - Romain Cosentino; Randall Balestriero; Yanis Bahroun; Anirvan M. Sengupta; Richard G. Baraniuk; Behnaam Aazhang (IEEECONF, 2022)

Toward a Geometrical Understanding of Self-supervised Contrastive Learning. - Romain Cosentino; Anirvan M. Sengupta; Salman Avestimehr; Mahdi Soltanolkotabi; Antonio Ortega; Theodore L. Willke; Mariano Tepper (CoRR, 2022)

The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning. - Romain Cosentino; Sarath Shekkizhar; Mahdi Soltanolkotabi; Salman Avestimehr; Antonio Ortega (CoRR, 2022)

Manifold Approximating Graph Interpolation of Cardiac Local Activation Time. - Jennifer Hellar; Romain Cosentino; Mathews M. John; Allison Post; Skylar Buchan; Mehdi Razavi; Behnaam Aazhang (IEEE Trans. Biomed. Eng., 2022)

Characterizing Large Language Model Geometry Solves Toxicity Detection and Generation. - Randall Balestriero; Romain Cosentino; Sarath Shekkizhar (CoRR, 2023)

Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation. - Randall Balestriero; Romain Cosentino; Sarath Shekkizhar (ICML, 2024)

Reasoning in Large Language Models: A Geometric Perspective. - Romain Cosentino; Sarath Shekkizhar (CoRR, 2024)

AGI Is Coming... Right After AI Learns to Play Wordle. - Sarath Shekkizhar; Romain Cosentino (CoRR, 2025)