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ORCIDArnab Kumar Mondal
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2020 – today
- 2025
[i21]Kusha Sareen, Daniel Levy, Arnab Kumar Mondal, Sékou-Oumar Kaba, Tara Akhound-Sadegh, Siamak Ravanbakhsh:
Symmetry-Aware Generative Modeling through Learned Canonicalization. CoRR abs/2501.07773 (2025)- 2024
- [j8]Chandra Bhushan Kumar
, Arnab Kumar Mondal, Manvir Bhatia, Bijaya Ketan Panigrahi, Tapan Kumar Gandhi:
Unravelling sleep patterns: Supervised contrastive learning with self-attention for sleep stage classification. Appl. Soft Comput. 167: 112298 (2024) - [j7]Arnab Kumar Mondal, Piyush Tiwary, Parag Singla, Prathosh A. P.:
SoLAD: Sampling Over Latent Adapter for Few Shot Generation. IEEE Signal Process. Lett. 31: 3174-3178 (2024) - [c17]Arnab Kumar Mondal, Stefano Alletto, Denis Tomè:
HumMUSS: Human Motion Understanding Using State Space Models. CVPR 2024: 2318-2330 - [c16]Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh:
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory. ICLR 2024 - [i20]Arnab Kumar Mondal, Stefano Alletto, Denis Tomè:
HumMUSS: Human Motion Understanding using State Space Models. CoRR abs/2404.10880 (2024) - [i19]Siba Smarak Panigrahi, Arnab Kumar Mondal:
Improved Canonicalization for Model Agnostic Equivariance. CoRR abs/2405.14089 (2024) - [i18]Sanket Gandhi, Atul, Samanyu Mahajan, Vishal Sharma, Rushil Gupta, Arnab Kumar Mondal, Parag Singla:
Learning Disentangled Representation in Object-Centric Models for Visual Dynamics Prediction via Transformers. CoRR abs/2407.03216 (2024) - 2023
- [j6]Arnab Kumar Mondal, Ajay Sailopal, Parag Singla, Prathosh AP:
SSDMM-VAE: variational multi-modal disentangled representation learning. Appl. Intell. 53(7): 8467-8481 (2023) - [j5]Arnab Kumar Mondal, Indu Joshi, Pravendra Singh, Prathosh AP:
Clustering Single-Cell RNA Sequence Data Using Information Maximized and Noise-Invariant Representations. IEEE ACM Trans. Comput. Biol. Bioinform. 20(3): 1983-1994 (2023) - [j4]Chandra Bhushan Kumar, Arnab Kumar Mondal, Manvir Bhatia, Bijaya Ketan Panigrahi, Tapan Kumar Gandhi:
Self-Supervised Representation Learning-Based OSA Detection Method Using Single-Channel ECG Signals. IEEE Trans. Instrum. Meas. 72: 1-15 (2023) - [j3]Arnab Bhattacharjee, Arnab Kumar Mondal, Ashu Verma, Sukumar Mishra, Tapan Kumar Saha:
Deep Latent Space Clustering for Detection of Stealthy False Data Injection Attacks Against AC State Estimation in Power Systems. IEEE Trans. Smart Grid 14(3): 2338-2351 (2023) - [c15]Arnab Kumar Mondal, Lakshya Singhal, Piyush Tiwary, Parag Singla, Prathosh AP:
Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders. AISTATS 2023: 3440-3465 - [c14]Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Ashish Goswami, Satyam Modi, Arnab Kumar Mondal, Dinesh Khandelwal, Dinesh Garg, Parag Singla:
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. EMNLP 2023: 2975-3007 - [c13]Arnab Kumar Mondal, Piyush Tiwary, Parag Singla, Prathosh AP:
Few-shot Cross-domain Image Generation via Inference-time Latent-code Learning. ICLR 2023 - [c12]Omar Salemohamed, Edoardo Cetin, Sai Rajeswar, Arnab Kumar Mondal:
Hyperbolic Deep Reinforcement Learning for Continuous Control. Tiny Papers @ ICLR 2023 - [c11]Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh:
Equivariance with Learned Canonicalization Functions. ICML 2023: 15546-15566 - [c10]Arnab Kumar Mondal, Siba Smarak Panigrahi, Oumar Kaba, Sai Mudumba, Siamak Ravanbakhsh:
Equivariant Adaptation of Large Pretrained Models. NeurIPS 2023 - [i17]Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Arnab Kumar Mondal, Dinesh Khandelwal, Parag Singla, Dinesh Garg:
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. CoRR abs/2305.14410 (2023) - [i16]Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh:
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory. CoRR abs/2306.11941 (2023) - [i15]Arnab Kumar Mondal, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh:
Equivariant Adaptation of Large Pretrained Models. CoRR abs/2310.01647 (2023) - 2022
- [j2]Arnab Kumar Mondal:
COVID-19 prognosis using limited chest X-ray images. Appl. Soft Comput. 122: 108867 (2022) - [j1]Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, Prathosh AP:
scRAE: Deterministic Regularized Autoencoders With Flexible Priors for Clustering Single-Cell Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 19(5): 2996-3007 (2022) - [c9]Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi, Siamak Ravanbakhsh:
EqR: Equivariant Representations for Data-Efficient Reinforcement Learning. ICML 2022: 15908-15926 - [c8]Kumar Krishna Agrawal, Arnab Kumar Mondal, Arna Ghosh, Blake A. Richards:
$\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay. NeurIPS 2022 - [c7]Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh:
Structuring Representations Using Group Invariants. NeurIPS 2022 - [i14]Arna Ghosh, Arnab Kumar Mondal, Kumar Krishna Agrawal, Blake A. Richards:
Investigating Power laws in Deep Representation Learning. CoRR abs/2202.05808 (2022) - [i13]Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh:
Transformation Coding: Simple Objectives for Equivariant Representations. CoRR abs/2202.10930 (2022) - [i12]Ayush Tripathi, Arnab Kumar Mondal, Lalan Kumar, Prathosh A. P.:
ImAiR : Airwriting Recognition framework using Image Representation of IMU Signals. CoRR abs/2205.01904 (2022) - [i11]Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh:
Equivariance with Learned Canonicalization Functions. CoRR abs/2211.06489 (2022) - 2021
- [c6]Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi:
Mini-batch Similarity Graphs for Robust Image Classification. BMVC 2021: 194 - [c5]Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, A. P. Prathosh:
FlexAE: flexibly learning latent priors for wasserstein auto-encoders. UAI 2021: 525-535 - [i10]Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi:
Mini-batch graphs for robust image classification. CoRR abs/2105.03237 (2021) - [i9]Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, Prathosh AP:
ScRAE: Deterministic Regularized Autoencoders with Flexible Priors for Clustering Single-cell Gene Expression Data. CoRR abs/2107.07709 (2021) - [i8]Ayush Tripathi, Arnab Kumar Mondal, Lalan Kumar, Prathosh A. P.:
SCLAiR : Supervised Contrastive Learning for User and Device Independent Airwriting Recognition. CoRR abs/2111.12938 (2021) - 2020
- [c4]Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Himanshu Asnani, Parag Singla, Prathosh A. P.:
MaskAAE: Latent space optimization for Adversarial Auto-Encoders. UAI 2020: 689-698 - [c3]Arnab Kumar Mondal, Arnab Bhattacharjee, Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan, Prathosh A. P.:
C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation. UAI 2020: 849-858 - [i7]Arnab Kumar Mondal, Arnab Bhattacharya, Sudipto Mukherjee, Sreeram Kannan, Himanshu Asnani, Prathosh AP:
C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation. CoRR abs/2005.08226 (2020) - [i6]Arnab Kumar Mondal, Himanshu Asnani, Parag Singla, Prathosh AP:
To Regularize or Not To Regularize? The Bias Variance Trade-off in Regularized AEs. CoRR abs/2006.05838 (2020) - [i5]Arnab Kumar Mondal, Pratheeksha Nair, Kaleem Siddiqi:
Group Equivariant Deep Reinforcement Learning. CoRR abs/2007.03437 (2020) - [i4]Arnab Kumar Mondal, Prathosh A. P.:
RespVAD: Voice Activity Detection via Video-Extracted Respiration Patterns. CoRR abs/2008.09466 (2020)
2010 – 2019
- 2019
- [i3]Arnab Kumar Mondal, Aniket Agarwal, Jose Dolz, Christian Desrosiers:
Revisiting CycleGAN for semi-supervised segmentation. CoRR abs/1908.11569 (2019) - [i2]Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Parag Singla, Himanshu Asnani, Prathosh A. P.:
Towards Latent Space Optimality for Auto-Encoder Based Generative Models. CoRR abs/1912.04564 (2019) - 2018
- [i1]Arnab Kumar Mondal, Jose Dolz, Christian Desrosiers:
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning. CoRR abs/1810.12241 (2018) - 2011
- [c2]Mohammed Nasir, Arnab Kumar Mondal, Soumyadip Sengupta, Swagatam Das, Ajith Abraham:
An improved Multiobjective Evolutionary Algorithm based on decomposition with fuzzy dominance. IEEE Congress on Evolutionary Computation 2011: 765-772 - [c1]Soumyadip Sengupta, Md. Nasir, Arnab Kumar Mondal, Swagatam Das:
An Improved Multi-Objective Algorithm Based on Decomposition with Fuzzy Dominance for Deployment of Wireless Sensor Networks. SEMCCO (1) 2011: 688-696
Coauthor Index
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