Concordance and consensus. - Cees H. Elzinga; Hui Wang 001; Zhiwei Lin 002; Yash Kumar (Inf. Sci., 2011)

Fault prediction and reliability analysis in a real cellular network. - Yash Kumar; Hasan Farooq; Ali Imran 001 (IWCMC, 2017)

GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations. - Yash Kumar; Souvik Chakraborty (CoRR, 2021)

ML-Based Analysis to Identify Speech Features Relevant in Predicting Alzheimer's Disease. - Yash Kumar; Piyush Maheshwari; Shreyansh Joshi; Veeky Baths (ICCAI, 2022)

Energy networks for state estimation with random sensors using sparse labels. - Yash Kumar; Souvik Chakraborty (CoRR, 2022)

Deep Convolutional Architectures for Extrapolative Forecast in Time-dependent Flow Problems. - Pratyush Bhatt; Yash Kumar; Azzeddine Soulaïmani (CoRR, 2022)

State estimation with limited sensors - A deep learning based approach. - Yash Kumar; Pranav Bahl; Souvik Chakraborty (J. Comput. Phys., 2022)

Preserving Heritage Palaces: A Deep Learning CNN-SVM Hybrid Approach for Multi-classification. - Deepak Kumar; Yash Kumar; Vinay Kukreja; Shanmugasundram Hariharan; Bhawna Goyal; Aditya Verma (ICCCNT, 2023)

The HRA Organ Gallery affords immersive superpowers for building and exploring the Human Reference Atlas with virtual reality. - Andreas Bueckle; Catherine Qing; Shefali Luley; Yash Kumar; Naval Pandey; Katy Börner (Frontiers Bioinform., 2023)

Deep convolutional architectures for extrapolative forecasts in time-dependent flow problems. - Pratyush Bhatt; Yash Kumar; Azzeddine Soulaïmani (Adv. Model. Simul. Eng. Sci., 2023)

Studying the capabilities of Large Language Models in solving Combinatorics Problems posed in Hindi. - Yash Kumar; Subhajit Roy 001 (COLING Workshops, 2025)

Energy network for state estimation with random sensors and sparse labels. - Yash Kumar; Tushar; Souvik Chakraborty (Comput. Phys. Commun., 2025)

Understanding Generalization, Robustness, and Interpretability in Low-Capacity Neural Networks. - Yash Kumar (CoRR, 2025)