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2020 – today
- 2024
[i10]Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho:
A Framework for Multi-modal Learning: Jointly Modeling Inter- & Intra-Modality Dependencies. CoRR abs/2405.17613 (2024)- 2023
- [c9]Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman:
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. ACL (1) 2023: 16334-16368 - [c8]Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov:
Heterogeneous Continual Learning. CVPR 2023: 15985-15995 - [c7]Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. MIDL 2023: 1726-1750 - [i9]Michael Sun, Ananya Kumar, Divyam Madaan, Percy Liang:
Improving Representational Continuity via Continued Pretraining. CoRR abs/2302.13289 (2023) - [i8]Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov:
Heterogeneous Continual Learning. CoRR abs/2306.08593 (2023) - [i7]Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. CoRR abs/2306.13276 (2023) - 2022
- [c6]Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang:
Representational Continuity for Unsupervised Continual Learning. ICLR 2022 - [c5]Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang:
Online Coreset Selection for Rehearsal-based Continual Learning. ICLR 2022 - [i6]Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman:
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. CoRR abs/2208.12852 (2022) - 2021
- [c4]Divyam Madaan, Jinwoo Shin, Sung Ju Hwang:
Learning to Generate Noise for Multi-Attack Robustness. ICML 2021: 7279-7289 - [i5]Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang:
Online Coreset Selection for Rehearsal-based Continual Learning. CoRR abs/2106.01085 (2021) - [i4]Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang:
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning. CoRR abs/2110.06976 (2021) - 2020
- [c3]Divyam Madaan, Jinwoo Shin, Sung Ju Hwang:
Adversarial Neural Pruning with Latent Vulnerability Suppression. ICML 2020: 6575-6585 - [i3]Divyam Madaan, Jinwoo Shin, Sung Ju Hwang:
Learning to Generate Noise for Robustness against Multiple Perturbations. CoRR abs/2006.12135 (2020)
2010 – 2019
- 2019
- [c2]Radhika Dua, Divyam Madaan, Prerana Mukherjee, Brejesh Lall:
Real Time Attention Based Bidirectional Long Short-Term Memory Networks for Air Pollution Forecasting. BigDataService 2019: 151-158 - [c1]Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall:
VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting. GlobalSIP 2019: 1-5 - [i2]Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall:
VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting. CoRR abs/1904.03977 (2019) - [i1]Divyam Madaan, Sung Ju Hwang:
Adversarial Neural Pruning. CoRR abs/1908.04355 (2019)
Coauthor Index
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