Publications
You can also find these papers on my Google Scholar profile.
HumMUSS: Human Motion understanding using State Space Models (CVPR 2024)
Arnab Mondal, Denis Tome, Stefano Alletto
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory (ICLR 2024)
Arnab Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh
Equivariant Adaptation of Large Pre-Trained Models (NeuRIPS 2023)
Arnab Mondal*, Siba Smarak Panigrahi*, Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh
Equivariance with Learned Canonicalization Functions (ICML 2023)
Oumar Kaba*, Arnab Mondal* , Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh
Hyperbolic Deep Reinforcement Learning for Continuous Control (ICLR 2023 Tiny paper track)
Omar Salemohamed, Edoardo Cetin, Sai Rajeswar, Arnab Kumar Mondal
Structuring Representations using Geometric Invariant (NeuRIPS 2022)
Mehran Shakerinava*, Arnab Mondal* , Siamak Ravanbakhsh
Assessing representation quality in Self-Supervised Learning by measuring eigenspectrum decay (NeuRIPS 2022)
Kumar Krishna Agrawal*, Arnab Mondal* ,Arna Ghosh*, Blake Richards
EqR: Equivariant Representations for Data-Efficient Reinforcement Learning (ICML 2022)
Code
Arnab Mondal ,Vineet Jain, Kaleem Siddiqi, Siamak Ravanbakhsh
Minibatch Graphs for Robust Image Classification and Generative Adversarial Learning (BMVC 2021)
Code
Arnab Mondal* , Vineet Jain*, Kaleem Siddiqi
Group Equivariant Deep Reinforcement Learning (ICML 2020 Workshop)
Code
Arnab Mondal , Pratheeksha Nair, Kaleem Siddiqi
Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach (ICIP 2020)
Avisek Lahiri*, Vineet Jain*, Arnab Mondal* , Prabir Kumar Biswas
Revisiting CycleGAN for semi-supervised segmentation (arxiv 2019) Code
Arnab Mondal, Aniket Agarwal , Jose Dolz, Christian Desrosiers
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning (arxiv 2018)
Code
Arnab Mondal , Jose Dolz, Christian Desrosiers
* denotes joint first author
Patents
Systems and methods for video retrieval and grounding (US Patent)
Arnab Mondal, Deepak Sridhar, Niamul Quader, Juwei Lu, Dai Pen, Chao Xing
Other technical articles
Generalization and Data Efficiency in Deep Learning
Arnab Mondal
Why Wasserstein distance is better for training GANs: A summary
Arnab Mondal
Semi-supervised Semantic Segmentation: Different GAN based approaches (Master’s Thesis)
Arnab Mondal