Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. - Eitan Borgnia; Valeriia Cherepanova; Liam Fowl; Amin Ghiasi; Jonas Geiping; Micah Goldblum; Tom Goldstein; Arjun Gupta (ICASSP, 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 (NeurIPS, 2021)

DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. - Eitan Borgnia; Jonas Geiping; Valeriia Cherepanova; Liam Fowl; Arjun Gupta; Amin Ghiasi; Furong Huang; Micah Goldblum; Tom Goldstein (CoRR, 2021)

Datasets for Studying Generalization from Easy to Hard Examples. - Avi Schwarzschild; Eitan Borgnia; Arjun Gupta; Arpit Bansal; Zeyad Emam; Furong Huang; Micah Goldblum; Tom Goldstein (CoRR, 2021)

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, 2022)

End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. - Arpit Bansal; Avi Schwarzschild; Eitan Borgnia; Zeyad Emam; Furong Huang; Micah Goldblum; Tom Goldstein (CoRR, 2022)

What do Vision Transformers Learn? A Visual Exploration. - Amin Ghiasi; Hamid Kazemi; Eitan Borgnia; Steven Reich; Manli Shu; Micah Goldblum; Andrew Gordon Wilson; Tom Goldstein (CoRR, 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 (ICLR, 2023)

Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. - Arpit Bansal; Eitan Borgnia; Hong-Min Chu; Jie Li 070; Hamid Kazemi; Furong Huang; Micah Goldblum; Jonas Geiping; Tom Goldstein (NeurIPS, 2023)