Learning Sparse Networks Using Targeted Dropout AN Gomez, I Zhang, SR Kamalakara, D Madaan, K Swersky, Y Gal, ... arXiv preprint arXiv:1905.13678, 2019 | 119 | 2019 |
Online Coreset Selection for Rehearsal-based Continual Learning J Yoon, D Madaan, E Yang, SJ Hwang arXiv preprint arXiv:2106.01085, 2021 | 113 | 2021 |
Representational Continuity for Unsupervised Continual Learning D Madaan, J Yoon, Y Li, Y Liu, SJ Hwang International Conference on Learning Representations, 2021 | 106 | 2021 |
Adversarial Neural Pruning with Latent Vulnerability Suppression D Madaan, J Shin, SJ Hwang 37th International Conference on Machine Learning, 2020 | 54 | 2020 |
Learning to Generate Noise for Multi-Attack Robustness D Madaan, J Shin, SJ Hwang 38th International Conference on Machine Learning, 2021 | 27* | 2021 |
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey J Michael, A Holtzman, A Parrish, A Mueller, A Wang, A Chen, D Madaan, ... arXiv preprint arXiv:2208.12852, 2022 | 18 | 2022 |
VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting D Madaan, R Dua, P Mukherjee, B Lall 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2019 | 15 | 2019 |
Heterogeneous Continual Learning D Madaan, H Yin, W Byeon, J Kautz, P Molchanov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 3 | 2023 |
TECHNIQUES FOR HETEROGENEOUS CONTINUAL LEARNING WITH MACHINE LEARNING MODEL ARCHITECTURE PROGRESSION H Yin, W Byeon, J Kautz, D Madaan, P Molchanov US Patent App. 18/348,286, 2024 | | 2024 |
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis D Madaan, D Sodickson, K Cho, S Chopra Medical Imaging with Deep Learning, 2023 | | 2023 |
Generalizable robust deep learning via adversarial pruning and meta-noise generation D Madaan 한국과학기술원, 2021 | | 2021 |
Separating Multimodal Modeling from Multidimensional Modeling for Multimodal Learning D Madaan, T Makino, S Chopra, K Cho | | |