Gowthami Somepalli

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Tom GoldsteinVolpi-Cupal Professor of Computer Science, University of MarylandZweryfikowany adres z cs.umd.edu
Micah GoldblumColumbia UniversityZweryfikowany adres z columbia.edu
Jonas GeipingELLIS Institute Tübingen & Max Planck Institute for Intelligent SystemsZweryfikowany adres z tuebingen.mpg.de
John KirchenbauerUniversity of Maryland, College ParkZweryfikowany adres z umd.edu
Avi SchwarzschildPost Doc at Carnegie Mellon UniversityZweryfikowany adres z cmu.edu
C. Bayan BrussCapital OneZweryfikowany adres z capitalone.com
Andrew Gordon WilsonNew York UniversityZweryfikowany adres z cims.nyu.edu
Liam FowlGoogleZweryfikowany adres z google.com
Abhinav ShrivastavaAssociate Professor, University of Maryland, College ParkZweryfikowany adres z cs.umd.edu
Michael MoellerProfessor for Computer Vision, University of Siegen, GermanyZweryfikowany adres z uni-siegen.de
Yehuda DarAssistant Professor of Computer Science, Ben-Gurion UniversityZweryfikowany adres z bgu.ac.il
Richard BaraniukC. Sidney Burrus Professor, Electrical & Computer Engineering, Rice UniversityZweryfikowany adres z rice.edu
Arpit BansalUniversity of Maryland, College ParkZweryfikowany adres z umd.edu
Kamal GuptaUniversity of Maryland, College ParkZweryfikowany adres z cs.umd.edu
David W. JacobsProfessor of Computer Science, University of MarylandZweryfikowany adres z umiacs.umd.edu
Ronen BasriProfessor of Computer Science, Weizmann Institute of ScienceZweryfikowany adres z weizmann.ac.il
Soheil FeiziUniversity of Maryland, College ParkZweryfikowany adres z cs.umd.edu
Yogesh BalajiResearch Scientist at NVIDIAZweryfikowany adres z nvidia.com
Ravid Shwartz-ZivNew York UniversityZweryfikowany adres z nyu.edu
Sridhar HannenhalliSenior Investigator, Cancer Data Science Lab, National Cancer Institute. NIHZweryfikowany adres z nih.gov

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Gowthami Somepalli

University of Maryland, College Park

Zweryfikowany adres z umd.edu - Strona główna

Machine Learning


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training G Somepalli, M Goldblum, A Schwarzschild, CB Bruss, T Goldstein NeurIPS 2022 Tabular Representation Learning Workshop, 2022	367*	2022
Baseline defenses for adversarial attacks against aligned language models N Jain, A Schwarzschild, Y Wen, G Somepalli, J Kirchenbauer, P Chiang, ... arXiv preprint arXiv:2309.00614, 2023	344*	2023
Diffusion art or digital forgery? investigating data replication in diffusion models G Somepalli, V Singla, M Goldblum, J Geiping, T Goldstein Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	325	2023
Understanding and Mitigating Copying in Diffusion Models G Somepalli, V Singla, M Goldblum, J Geiping, T Goldstein Advances in Neural Information Processing Systems 36, 2023	118	2023
What doesn't kill you makes you robust (er): How to adversarially train against data poisoning J Geiping, L Fowl, G Somepalli, M Goldblum, M Moeller, T Goldstein arXiv preprint arXiv:2102.13624, 2021	87	2021
Neftune: Noisy embeddings improve instruction finetuning N Jain, P Chiang, Y Wen, J Kirchenbauer, HM Chu, G Somepalli, ... arXiv preprint arXiv:2310.05914, 2023	76*	2023
Can neural nets learn the same model twice? investigating reproducibility and double descent from the decision boundary perspective G Somepalli, L Fowl, A Bansal, P Yeh-Chiang, Y Dar, R Baraniuk, ... Proceedings of the ieee/cvf conference on computer vision and pattern …, 2022	75	2022
Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks M Goldblum, H Souri, R Ni, M Shu, V Prabhu, G Somepalli, ... Advances in Neural Information Processing Systems 36, 29343-29371, 2023	65	2023
How much data are augmentations worth? An investigation into scaling laws, invariance, and implicit regularization J Geiping, M Goldblum, G Somepalli, R Shwartz-Ziv, T Goldstein, ... ICLR 2023, 2022	40	2022
Avi Schwarzschild, C G Somepalli, M Goldblum Bayan Bruss, and Tom Goldstein. Saint: Improved neural networks for tabular …, 2021	29	2021
Cinepile: A long video question answering dataset and benchmark R Rawal, K Saifullah, M Farré, R Basri, D Jacobs, G Somepalli, ... arXiv preprint arXiv:2405.08813, 2024	27	2024
Measuring Style Similarity in Diffusion Models G Somepalli, A Gupta, K Gupta, S Palta, M Goldblum, J Geiping, ... European Conference on Computer Vision, 2025, 2024	22	2024
Be like a goldfish, don't memorize! mitigating memorization in generative llms A Hans, J Kirchenbauer, Y Wen, N Jain, H Kazemi, P Singhania, S Singh, ... Advances in Neural Information Processing Systems 37, 24022-24045, 2025	19*	2025
Unsupervised Anomaly Detection with Adversarial Mirrored AutoEncoders G Somepalli, Y Wu, Y Balaji, B Vinzamuri, S Feizi Uncertainty in Artificial Intelligence, PMLR 161:365-375, 2021	19*	2021
A performance-driven benchmark for feature selection in tabular deep learning V Cherepanova, R Levin, G Somepalli, J Geiping, CB Bruss, AG Wilson, ... Advances in Neural Information Processing Systems 36, 41956-41979, 2023	16	2023
From pixels to prose: A large dataset of dense image captions V Singla, K Yue, S Paul, R Shirkavand, M Jayawardhana, A Ganjdanesh, ... arXiv preprint arXiv:2406.10328, 2024	15	2024
Prioritizing and characterizing functionally relevant genes across human tissues G Somepalli, S Sahoo, A Singh, S Hannenhalli PLoS Computational Biology 17 (7), e1009194, 2021	9	2021
Lmd3: Language model data density dependence J Kirchenbauer, G Honke, G Somepalli, J Geiping, D Ippolito, K Lee, ... arXiv preprint arXiv:2405.06331, 2024	7	2024
Patchgame: Learning to signal mid-level patches in referential games K Gupta, G Somepalli, A Anubhav, VYJ Magalle Hewa, M Zwicker, ... Advances in Neural Information Processing Systems 34, 26015-26027, 2021	7	2021
Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models R Shirkavand, P Yu, S Gao, G Somepalli, T Goldstein, H Huang arXiv preprint arXiv:2412.15341, 2024		2024

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