Divyam Madaan

25 papers A* 6Journal 14Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Characterizing the Predictive Impact of Modalities with Supervised Latent-Variable Modeling.
CoRR
Divyam Madaan, Sumit Chopra, Kyunghyun Cho
2025 J jnl
Multi-modal Data Spectrum: Multi-modal Datasets are Multi-dimensional.
CoRR
Divyam Madaan, Varshan Muhunthan, Kyunghyun Cho, Sumit Chopra
2025 J jnl
Temporal Generalization: A Reality Check.
CoRR
Divyam Madaan, Sumit Chopra, Kyunghyun Cho
2024 J jnl
A Framework for Multi-modal Learning: Jointly Modeling Inter- & Intra-Modality Dependencies.
CoRR
Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho
2024 — conf
HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis.
ML4H@NeurIPS
Haoxu Huang, Cem M. Deniz, Kyunghyun Cho, Sumit Chopra, Divyam Madaan
2024 J jnl
HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis.
CoRR
Haoxu Huang, Cem M. Deniz, Kyunghyun Cho, Sumit Chopra, Divyam Madaan
2024 A* conf
Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning.
NeurIPS
Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho
2023 A* conf
Heterogeneous Continual Learning.
CVPR
Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov
2023 J jnl
Heterogeneous Continual Learning.
CoRR
Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov
2023 J jnl
Improving Representational Continuity via Continued Pretraining.
CoRR
Michael Sun, Ananya Kumar, Divyam Madaan, Percy Liang
2023 — conf
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis.
MIDL
Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra
2023 J jnl
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis.
CoRR
Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra
2023 — conf
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey.
ACL (1)
Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
2022 A* conf
Online Coreset Selection for Rehearsal-based Continual Learning.
ICLR
Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang
2022 A* conf
Representational Continuity for Unsupervised Continual Learning.
ICLR
Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang
2022 J jnl
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey.
CoRR
Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
2021 A* conf
Learning to Generate Noise for Multi-Attack Robustness.
ICML
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
2021 J jnl
Online Coreset Selection for Rehearsal-based Continual Learning.
CoRR
Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang
2021 J jnl
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning.
CoRR
Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang
2020 A* conf
Adversarial Neural Pruning with Latent Vulnerability Suppression.
ICML
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
2020 J jnl
Learning to Generate Noise for Robustness against Multiple Perturbations.
CoRR
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
2019 J jnl
Adversarial Neural Pruning.
CoRR
Divyam Madaan, Sung Ju Hwang
2019 — conf
Real Time Attention Based Bidirectional Long Short-Term Memory Networks for Air Pollution Forecasting.
BigDataService
Radhika Dua, Divyam Madaan, Prerana Mukherjee, Brejesh Lall
2019 — conf
VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting.
GlobalSIP
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall
2019 J jnl
VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting.
CoRR
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall