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Romain Cosentino
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2020 – today
- 2024
- [c8]Randall Balestriero, Romain Cosentino, Sarath Shekkizhar:
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation. ICML 2024 - [i10]Romain Cosentino, Sarath Shekkizhar:
Reasoning in Large Language Models: A Geometric Perspective. CoRR abs/2407.02678 (2024) - 2023
- [i9]Randall Balestriero, Romain Cosentino, Sarath Shekkizhar:
Characterizing Large Language Model Geometry Solves Toxicity Detection and Generation. CoRR abs/2312.01648 (2023) - 2022
- [j3]Jennifer Hellar, Romain Cosentino, Mathews M. John, Allison Post, Skylar Buchan, Mehdi Razavi, Behnaam Aazhang:
Manifold Approximating Graph Interpolation of Cardiac Local Activation Time. IEEE Trans. Biomed. Eng. 69(10): 3253-3264 (2022) - [c7]Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang:
Spatial Transformer K-Means. IEEECONF 2022: 1444-1448 - [i8]Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang:
Spatial Transformer K-Means. CoRR abs/2202.07829 (2022) - [i7]Romain Cosentino, Anirvan M. Sengupta, Salman Avestimehr, Mahdi Soltanolkotabi, Antonio Ortega, Theodore L. Willke, Mariano Tepper:
Toward a Geometrical Understanding of Self-supervised Contrastive Learning. CoRR abs/2205.06926 (2022) - [i6]Romain Cosentino, Sarath Shekkizhar, Mahdi Soltanolkotabi, Salman Avestimehr, Antonio Ortega:
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning. CoRR abs/2209.08622 (2022) - 2021
- [j2]Anton Banta, Romain Cosentino, Mathews John, Allison Post, Skylar Buchan, Mehdi Razavi, Behnaam Aazhang:
A novel convolutional neural network for reconstructing surface electrocardiograms from intracardiac electrograms and vice versa. Artif. Intell. Medicine 118: 102135 (2021) - [c6]Jennifer Hellar, Romain Cosentino, Mathews M. John, Allison Post, Skylar Buchan, Mehdi Razavi, Behnaam Aazhang:
Graph-Based Interpolation of Local Activation Time on the Cardiac Surface. ACSCC 2021: 274-278 - [c5]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang:
Deep Autoencoders: From Understanding to Generalization Guarantees. MSML 2021: 197-222 - 2020
- [j1]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang:
Universal Frame Thresholding. IEEE Signal Process. Lett. 27: 1115-1119 (2020) - [c4]Romain Cosentino, Behnaam Aazhang:
Learnable Group Transform For Time-Series. ICML 2020: 2164-2173 - [i5]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang:
Provable Finite Data Generalization with Group Autoencoder. CoRR abs/2009.09525 (2020) - [i4]Romain Cosentino, Randall Balestriero:
Sparse Multi-Family Deep Scattering Network. CoRR abs/2012.07662 (2020) - [i3]Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang:
Interpretable Image Clustering via Diffeomorphism-Aware K-Means. CoRR abs/2012.09743 (2020)
2010 – 2019
- 2019
- [c3]Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk:
The Geometry of Deep Networks: Power Diagram Subdivision. NeurIPS 2019: 15806-15815 - [i2]Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk:
The Geometry of Deep Networks: Power Diagram Subdivision. CoRR abs/1905.08443 (2019) - 2018
- [c2]Randall Balestriero, Romain Cosentino, Hervé Glotin, Richard G. Baraniuk:
Spline Filters For End-to-End Deep Learning. ICML 2018: 373-382 - 2017
- [i1]Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Ankit B. Patel:
Overcomplete Frame Thresholding for Acoustic Scene Analysis. CoRR abs/1712.09117 (2017) - 2016
- [c1]Romain Cosentino, Randall Balestriero, Behnaam Aazhang:
Best basis selection using sparsity driven multi-family wavelet transform. GlobalSIP 2016: 252-256
Coauthor Index
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last updated on 2024-09-04 01:24 CEST by the dblp team
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