PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python. - Haiping Lu; Xianyuan Liu; Robert Turner; Peizhen Bai; Raivo E. Koot; Shuo Zhou; Mustafa Chasmai; Lawrence Schobs (CoRR, 2021)

PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python. - Haiping Lu; Xianyuan Liu; Shuo Zhou; Robert Turner; Peizhen Bai; Raivo E. Koot; Mustafa Chasmai; Lawrence Schobs; Hao Xu (CIKM, 2022)

Representation Learning Using Rank Loss for Robust Neurosurgical Skills Evaluation. - Britty Baby; Mustafa Chasmai; Tamajit Banerjee; Ashish Suri; Subhashis Banerjee; Chetan Arora 001 (ICIP, 2022)

Adversarially Robust Prototypical Few-Shot Segmentation with Neural-ODEs. - Prashant Pandey 002; Aleti Vardhan; Mustafa Chasmai; Tanuj Sur; Brejesh Lall (MICCAI (8), 2022)

Person Re-Identification. - Mustafa Ebrahim Chasmai; Tamajit Banerjee (CoRR, 2022)

A View Independent Classification Framework for Yoga Postures. - Mustafa Chasmai; Nirjhar Das; Aman Bhardwaj; Rahul Garg 001 (SN Comput. Sci., 2022)

Weakly Supervised Few-Shot and Zero-Shot Semantic Segmentation with Mean Instance Aware Prompt Learning. - Prashant Pandey 002; Mustafa Chasmai; Monish Natarajan; Brejesh Lall (ICME, 2023)

From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments. - Britty Baby; Daksh Thapar; Mustafa Chasmai; Tamajit Banerjee; Kunal Dargan; Ashish Suri; Subhashis Banerjee; Chetan Arora 001 (WACV, 2023)

A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation. - Prashant Pandey 002; Mustafa Chasmai; Monish Natarajan; Brejesh Lall (CoRR, 2023)

Robust Prototypical Few-Shot Organ Segmentation With Regularized Neural-ODEs. - Prashant Pandey 002; Mustafa Chasmai; Tanuj Sur; Brejesh Lall (IEEE Trans. Medical Imaging, 2023)

The iNaturalist Sounds Dataset. - Mustafa Chasmai; Alexander Shepard; Subhransu Maji; Grant Van Horn (NeurIPS, 2024)

Audio Geolocation: A Natural Sounds Benchmark. - Mustafa Chasmai; Wuao Liu; Subhransu Maji; Grant Van Horn (CoRR, 2025)

Moment Sampling in Video LLMs for Long-Form Video QA. - Mustafa Chasmai; Gauri Jagatap; Gouthaman KV; Grant Van Horn; Subhransu Maji; Andrea Fanelli (CoRR, 2025)