Randall Balestriero - Concepedia

Author

Randall Balestriero

Rice University ORCID

Also Known As

Balestriero, Randall, Baraniuk, Richard, Gamba, Matteo, Randall Balestriero, You, Haoran

145

Publications

913

Citations

H-Index

Concepts

All Affiliations

Rice University Université Grenoble Alpes Centre National de la Recherche Scientifique Institut des Sciences de la Terre

About

Randall Balestriero is an author at Rice University specializing in engineering, machine learning, and data science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	11	12	370
2	Computer Science	9	9	308
3	Computer Engineering	2	2	57
4	Education	1	1	161
5	Health Sciences	1	1	10

Randall Balestriero

Publications

694

Citations

H-Index

Page 1

	Year	Citations
Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning Léonard Seydoux, Randall Balestriero, Piero Poli, Nature Communications	2020	198
A Cookbook of Self-Supervised Learning Randall Balestriero, Mark Ibrahim, Vlad Sobal, arXiv (Cornell University) Artificial IntelligenceEngineeringMachine LearningMachine Learning ToolEducation	2023	161
The Effects of Regularization and Data Augmentation are Class Dependent Randall Balestriero, Léon Bottou, Yann LeCun arXiv (Cornell University) Convolutional Neural NetworkEngineeringMachine LearningWeight DecayHuman Augmentation	2022	39
Anatomy of Continuous Mars SEIS and Pressure Data from Unsupervised Learning Salma Barkaoui, Philippe Lognonné, Taïchi Kawamura, Bulletin of the Seismological Society of America EngineeringSeismic WaveDeep Scattering NetworkPlanetary GeologyGeophysical Signal Processing	2021	29
Learning in High Dimension Always Amounts to Extrapolation Randall Balestriero, Jerome Pesenti, Yann LeCun arXiv (Cornell University)	2021	26
DeepTensor: Low-Rank Tensor Decomposition With Deep Network Priors Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan, IEEE Transactions on Pattern Analysis and Machine Intelligence	2024	24
A spline theory of deep networks Richard G. Baraniuk, Randall Balestriero Geometric LearningEngineeringMachine VisionMachine LearningSparse Neural Network	2018	23
Mad Max: Affine Spline Insights Into Deep Learning Randall Balestriero, Richard G. Baraniuk Proceedings of the IEEE Geometric LearningConvolutional Neural NetworkVector QuantizationEngineeringMachine Learning	2020	22
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods Randall Balestriero, Yann LeCun arXiv (Cornell University) Spectral TheoryGeometric LearningEngineeringMachine LearningData Science	2022	22
Neural Decision Trees Randall Balestriero arXiv (Cornell University)	2017	19

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