Eitan Borgnia - RankMe

15 papers A* 5Misc 1Journal 9

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. ICLR Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. NeurIPS Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	J	`jnl`	Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. CoRR Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	J	`jnl`	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. CoRR Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	A*	`conf`	End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking. NeurIPS Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. CoRR Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	What do Vision Transformers Learn? A Visual Exploration. CoRR Amin Ghiasi, Hamid Kazemi, Eitan Borgnia, Steven Reich, Manli Shu, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein
2022	A*	`conf`	Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability. NeurIPS Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein
2021	A*	`conf`	Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks. NeurIPS Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein
2021	J	`jnl`	Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks. CoRR Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein
2021	J	`jnl`	DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein
2021	J	`jnl`	Datasets for Studying Generalization from Easy to Hard Examples. CoRR Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Arpit Bansal, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein
2021	Misc	`conf`	Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. ICASSP Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
2021	J	`jnl`	Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability. CoRR Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein
2020	J	`jnl`	Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. CoRR Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta