Romain Cosentino

According to our database, Romain Cosentino authored at least 19 papers between 2016 and 2024.

Collaborative distances:

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

2024

Reasoning in Large Language Models: A Geometric Perspective.

Romain Cosentino, Sarath Shekkizhar

CoRR, 2024

Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation.

Randall Balestriero, Romain Cosentino, Sarath Shekkizhar

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

2023

Characterizing Large Language Model Geometry Solves Toxicity Detection and Generation.

Randall Balestriero, Romain Cosentino, Sarath Shekkizhar

CoRR, 2023

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

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

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

Spatial Transformer K-Means.

Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

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

Deep Autoencoders: From Understanding to Generalization Guarantees.

Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang

Proceedings of the Mathematical and Scientific Machine Learning, 2021

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

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Universal Frame Thresholding.

Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang

IEEE Signal Process. Lett., 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

Sparse Multi-Family Deep Scattering Network.

Romain Cosentino, Randall Balestriero

CoRR, 2020

Provable Finite Data Generalization with Group Autoencoder.

Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang

CoRR, 2020

Learnable Group Transform For Time-Series.

Romain Cosentino, Behnaam Aazhang

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

2019

The Geometry of Deep Networks: Power Diagram Subdivision.

Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk

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

2018

Spline Filters For End-to-End Deep Learning.

Randall Balestriero, Romain Cosentino, Hervé Glotin, Richard G. Baraniuk

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Overcomplete Frame Thresholding for Acoustic Scene Analysis.

Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Ankit B. Patel

CoRR, 2017

2016

Best basis selection using sparsity driven multi-family wavelet transform.

Romain Cosentino, Randall Balestriero, Behnaam Aazhang

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016