Borgnia, Eitan

7 publications

ICLR 2023 Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein

NeurIPS 2023 Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein

NeurIPSW 2022 Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein

NeurIPSW 2022 DP-InstaHide: Data Augmentations Provably Enhance Guarantees Against Dataset Manipulations Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam H Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein

NeurIPS 2022 End-to-End Algorithm Synthesis with Recurrent Networks: Extrapolation Without Overthinking Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein

NeurIPS 2022 Where Do Models Go Wrong? Parameter-Space Saliency Maps for Explainability Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein

NeurIPS 2021 Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein