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Arpit Bansal
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2020 – today
- 2024
- [c10]Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Universal Guidance for Diffusion Models. ICLR 2024 - [i14]Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum:
Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion. CoRR abs/2403.16365 (2024) - [i13]Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein:
Transformers Can Do Arithmetic with the Right Embeddings. CoRR abs/2405.17399 (2024) - [i12]Ravid Shwartz-Ziv, Micah Goldblum, Arpit Bansal, C. Bayan Bruss, Yann LeCun, Andrew Gordon Wilson:
Just How Flexible are Neural Networks in Practice? CoRR abs/2406.11463 (2024) - 2023
- [c9]Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Universal Guidance for Diffusion Models. CVPR Workshops 2023: 843-852 - [c8]Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein:
Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent. ICLR 2023 - [c7]Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum:
Transfer Learning with Deep Tabular Models. ICLR 2023 - [c6]Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. ICLR 2023 - [c5]Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. NeurIPS 2023 - [i11]Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Universal Guidance for Diffusion Models. CoRR abs/2302.07121 (2023) - 2022
- [c4]Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein:
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR 2022: 13689-13698 - [c3]Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein:
Certified Neural Network Watermarks with Randomized Smoothing. ICML 2022: 1450-1465 - [c2]Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein:
End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking. NeurIPS 2022 - [i10]Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein:
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. CoRR abs/2202.05826 (2022) - [i9]Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein:
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR abs/2203.08124 (2022) - [i8]Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum:
Transfer Learning with Deep Tabular Models. CoRR abs/2206.15306 (2022) - [i7]Arpit Bansal, Ping-yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein:
Certified Neural Network Watermarks with Randomized Smoothing. CoRR abs/2207.07972 (2022) - [i6]Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. CoRR abs/2208.09392 (2022) - [i5]Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. CoRR abs/2210.10750 (2022) - 2021
- [i4]Liam Fowl, Ping-yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein:
Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release. CoRR abs/2103.02683 (2021) - [i3]Arpit Bansal, Micah Goldblum, Valeriia Cherepanova, Avi Schwarzschild, C. Bayan Bruss, Tom Goldstein:
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data. CoRR abs/2106.09643 (2021) - [i2]Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Arpit Bansal, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein:
Datasets for Studying Generalization from Easy to Hard Examples. CoRR abs/2108.06011 (2021)
2010 – 2019
- 2019
- [i1]Arpit Bansal, Sankaraganesh Jonna, Rajiv R. Sahay:
PAG-Net: Progressive Attention Guided Depth Super-resolution Network. CoRR abs/1911.09878 (2019) - 2018
- [j1]Vishwas Mahesh
, Vinyas Mahesh
, Ishwarkumar Teggi, Arpit Bansal, S. Manjesh:
Product design methodology applied in developing a liquid petroleum gas level indicator using android technology. Ingénierie des Systèmes d Inf. 23(5): 175-184 (2018) - 2016
- [c1]Arpit Bansal, Aashwin Vats, Akshita Jain, Malay Kishore Dutta
, Radim Burget, Jiri Prinosil:
An efficient automatic intensity based method for detection of macula in retinal images. TSP 2016: 507-510
Coauthor Index
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last updated on 2024-08-08 19:14 CEST by the dblp team
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