activity
20192026
most citedHeterogeneous Continual Learning

1 citations · 2 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

Characterizing the Predictive Impact of Modalities with Supervised Latent-Variable Modeling

Divyam Madaan, Sumit Chopra, Kyunghyun Cho

Despite the recent success of Multimodal Large Language Models (MLLMs), existing approaches predominantly assume the availability of multiple modalities during training and inferen…

cs.CV2025

Multi-modal Data Spectrum: Multi-modal Datasets are Multi-dimensional

Divyam Madaan, Varshan Muhunthan, Kyunghyun Cho +1

Understanding the interplay between intra-modality dependencies (the contribution of an individual modality to a target task) and inter-modality dependencies (the relationships bet…

cs.CV2024

Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning

Divyam Madaan, Taro Makino, Sumit Chopra +1

Supervised multi-modal learning involves mapping multiple modalities to a target label. Previous studies in this field have concentrated on capturing in isolation either the inter-…

cs.CV2023★ 1 cited

Heterogeneous Continual Learning

Divyam Madaan, Hongxu Yin, Wonmin Byeon +2

We propose a novel framework and a solution to tackle the continual learning (CL) problem with changing network architectures. Most CL methods focus on adapting a single architectu…

cs.CV2019

VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting

Divyam Madaan, Radhika Dua, Prerana Mukherjee +1

Air pollution is the leading environmental health hazard globally due to various sources which include factory emissions, car exhaust and cooking stoves. As a precautionary measure…