| Combinatorial optimization by graph pointer networks and hierarchical reinforcement learning Q Ma, S Ge, D He, D Thaker, I Drori arXiv preprint arXiv:1911.04936, 2019 | 225 | 2019 |
| Accurate protein structure prediction by embeddings and deep learning representations I Drori, D Thaker, A Srivatsa, D Jeong, Y Wang, L Nan, F Wu, D Leggas, ... arXiv preprint arXiv:1911.05531, 2019 | 7 | 2019 |
| Reverse Engineering attacks: A block-sparse optimization approach with recovery guarantees D Thaker, P Giampouras, R Vidal International Conference on Machine Learning, 21253-21271, 2022 | 6 | 2022 |
| PaCE: Parsimonious Concept Engineering for Large Language Models J Luo, T Ding, KHR Chan, D Thaker, A Chattopadhyay, C Callison-Burch, ... arXiv preprint arXiv:2406.04331, 2024 | | 2024 |
| A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions D Thaker, P Giampouras, R Vidal arXiv preprint arXiv:2306.04756, 2023 | | 2023 |
| Understanding the Convergence of Adversarial Training for Overparameterized Linear Neural Networks DB Thaker Columbia University, 0 | | |
Rene VidalRachleff University Professor, University of Pennsylvania; Amazon Scholar; Chief Scientist, NORCE在 seas.upenn.edu 的电子邮件经过验证
