Arnab Kumar Mondal

According to our database, Arnab Kumar Mondal authored at least 36 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Deep Latent Space Clustering for Detection of Stealthy False Data Injection Attacks Against AC State Estimation in Power Systems.

Arnab Bhattacharjee, Arnab Kumar Mondal, Ashu Verma, Sukumar Mishra, Tapan Kumar Saha

IEEE Trans. Smart Grid, May, 2023

SSDMM-VAE: variational multi-modal disentangled representation learning.

Arnab Kumar Mondal, Ajay Sailopal, Parag Singla, Prathosh AP

Appl. Intell., April, 2023

Self-Supervised Representation Learning-Based OSA Detection Method Using Single-Channel ECG Signals.

Chandra Bhushan Kumar, Arnab Kumar Mondal, Manvir Bhatia, Bijaya Ketan Panigrahi, Tapan Kumar Gandhi

IEEE Trans. Instrum. Meas., 2023

Clustering Single-Cell RNA Sequence Data Using Information Maximized and Noise-Invariant Representations.

Arnab Kumar Mondal, Indu Joshi, Pravendra Singh, Prathosh AP

IEEE ACM Trans. Comput. Biol. Bioinform., 2023

Equivariant Adaptation of Large Pretrained Models.

Arnab Kumar Mondal, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh

CoRR, 2023

Efficient Dynamics Modeling in Interactive Environments with Koopman Theory.

Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh

CoRR, 2023

Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach.

Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Arnab Kumar Mondal, Dinesh Khandelwal, Parag Singla, Dinesh Garg

CoRR, 2023

Equivariant Adaptation of Large Pretrained Models.

Arnab Kumar Mondal, Siba Smarak Panigrahi, Oumar Kaba, Sai Mudumba, Siamak Ravanbakhsh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Equivariance with Learned Canonicalization Functions.

Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh

Proceedings of the International Conference on Machine Learning, 2023

Hyperbolic Deep Reinforcement Learning for Continuous Control.

Omar Salemohamed, Edoardo Cetin, Sai Rajeswar, Arnab Kumar Mondal

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Few-shot Cross-domain Image Generation via Inference-time Latent-code Learning.

Arnab Kumar Mondal, Piyush Tiwary, Parag Singla, Prathosh AP

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach.

Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Ashish Goswami, Satyam Modi, Arnab Kumar Mondal, Dinesh Khandelwal, Dinesh Garg, Parag Singla

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders.

Arnab Kumar Mondal, Lakshya Singhal, Piyush Tiwary, Parag Singla, Prathosh AP

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

scRAE: Deterministic Regularized Autoencoders With Flexible Priors for Clustering Single-Cell Gene Expression Data.

Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, Prathosh AP

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

ImAiR : Airwriting Recognition framework using Image Representation of IMU Signals.

Ayush Tripathi, Arnab Kumar Mondal, Lalan Kumar, Prathosh A. P.

CoRR, 2022

Transformation Coding: Simple Objectives for Equivariant Representations.

Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh

CoRR, 2022

Investigating Power laws in Deep Representation Learning.

Arna Ghosh, Arnab Kumar Mondal, Kumar Krishna Agrawal, Blake A. Richards

CoRR, 2022

COVID-19 prognosis using limited chest X-ray images.

Arnab Kumar Mondal

Appl. Soft Comput., 2022

Structuring Representations Using Group Invariants.

Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

$\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay.

Kumar Krishna Agrawal, Arnab Kumar Mondal, Arna Ghosh, Blake A. Richards

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

EqR: Equivariant Representations for Data-Efficient Reinforcement Learning.

Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi, Siamak Ravanbakhsh

Proceedings of the International Conference on Machine Learning, 2022

2021

SCLAiR : Supervised Contrastive Learning for User and Device Independent Airwriting Recognition.

Ayush Tripathi, Arnab Kumar Mondal, Lalan Kumar, Prathosh A. P.

CoRR, 2021

Mini-batch graphs for robust image classification.

Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi

CoRR, 2021

FlexAE: flexibly learning latent priors for wasserstein auto-encoders.

Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, A. P. Prathosh

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Mini-batch Similarity Graphs for Robust Image Classification.

Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

RespVAD: Voice Activity Detection via Video-Extracted Respiration Patterns.

Arnab Kumar Mondal, Prathosh A. P.

CoRR, 2020

Group Equivariant Deep Reinforcement Learning.

Arnab Kumar Mondal, Pratheeksha Nair, Kaleem Siddiqi

CoRR, 2020

To Regularize or Not To Regularize? The Bias Variance Trade-off in Regularized AEs.

Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, Prathosh AP

CoRR, 2020

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation.

Arnab Kumar Mondal, Arnab Bhattacharya, Sudipto Mukherjee, Sreeram Kannan, Himanshu Asnani, Prathosh AP

CoRR, 2020

MaskAAE: Latent space optimization for Adversarial Auto-Encoders.

Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Himanshu Asnani, Parag Singla, Prathosh A. P.

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation.

Arnab Kumar Mondal, Arnab Bhattacharjee, Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan, Prathosh A. P.

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Towards Latent Space Optimality for Auto-Encoder Based Generative Models.

Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Parag Singla, Himanshu Asnani, Prathosh A. P.

CoRR, 2019

Revisiting CycleGAN for semi-supervised segmentation.

Arnab Kumar Mondal, Aniket Agarwal, Jose Dolz, Christian Desrosiers

CoRR, 2019

2018

Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning.

Arnab Kumar Mondal, Jose Dolz, Christian Desrosiers

CoRR, 2018

2011

An Improved Multi-Objective Algorithm Based on Decomposition with Fuzzy Dominance for Deployment of Wireless Sensor Networks.

Soumyadip Sengupta, Md. Nasir, Arnab Kumar Mondal, Swagatam Das

Proceedings of the Swarm, Evolutionary, and Memetic Computing, 2011

An improved Multiobjective Evolutionary Algorithm based on decomposition with fuzzy dominance.

Mohammed Nasir, Arnab Kumar Mondal, Soumyadip Sengupta, Swagatam Das, Ajith Abraham

Proceedings of the IEEE Congress on Evolutionary Computation, 2011