Minimum Distance Estimation of Milky Way Model Parameters and Related Inference. - Sourabh Banerjee; Ayanendranath Basu; Sourabh Bhattacharya; Smarajit Bose; Dalia Chakrabarty; Soumendu Sundar Mukherjee (SIAM/ASA J. Uncertain. Quantification, 2015)

On clustering network-valued data. - Soumendu Sundar Mukherjee; Purnamrita Sarkar; Lizhen Lin (NIPS, 2017)

Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues. - Soumendu Sundar Mukherjee; Purnamrita Sarkar; Y. X. Rachel Wang; Bowei Yan (NeurIPS, 2018)

On Some Inference Problems for Networks. - Soumendu Sundar Mukherjee (2018)

Graphon Estimation from Partially Observed Network Data. - Soumendu Sundar Mukherjee; Sayak Chakrabarti (CoRR, 2019)

Consistent detection and optimal localization of all detectable change points in piecewise stationary arbitrarily sparse network-sequences. - Sharmodeep Bhattacharyya; Shirshendu Chatterjee; Soumendu Sundar Mukherjee (CoRR, 2020)

Changepoint Analysis of Topic Proportions in Temporal Text Data. - Avinandan Bose; Soumendu Sundar Mukherjee (CoRR, 2021)

When random initializations help: a study of variational inference for community detection. - Purnamrita Sarkar; Y. X. Rachel Wang; Soumendu Sundar Mukherjee (J. Mach. Learn. Res., 2021)

Morphological Network: How Far Can We Go with Morphological Neurons? - Ranjan Mondal; Sanchayan Santra; Soumendu Sundar Mukherjee; Bhabatosh Chanda (BMVC, 2022)

Learning with latent group sparsity via heat flow dynamics on networks. - Subhroshekhar Ghosh; Soumendu Sundar Mukherjee (CoRR, 2022)

Wasserstein Projection Pursuit of Non-Gaussian Signals. - Satyaki Mukherjee; Soumendu Sundar Mukherjee; Debarghya Ghoshdastidar (CoRR, 2023)

Consistent model selection in the spiked Wigner model via AIC-type criteria. - Soumendu Sundar Mukherjee (CoRR, 2023)

Learning Networks from Gaussian Graphical Models and Gaussian Free Fields. - Subhro Ghosh; Soumendu Sundar Mukherjee; Hoang Son Tran; Ujan Gangopadhyay (CoRR, 2023)

Minimax-optimal estimation for sparse multi-reference alignment with collision-free signals. - Subhro Ghosh; Soumendu Sundar Mukherjee; Jing Bin Pan (CoRR, 2023)

Transfer Learning for Latent Variable Network Models. - Akhil Jalan; Arya Mazumdar; Soumendu Sundar Mukherjee; Purnamrita Sarkar (NeurIPS, 2024)

Implicit Regularization via Spectral Neural Networks and Non-linear Matrix Sensing. - Hong T. M. Chu; Subhro Ghosh; Chi Thanh Lam; Soumendu Sundar Mukherjee (CoRR, 2024)

LASER: A new method for locally adaptive nonparametric regression. - Sabyasachi Chatterjee; Subhajit Goswami; Soumendu Sundar Mukherjee (CoRR, 2024)

Changepoint Estimation in Sparse Dynamic Stochastic Block Models under Near-Optimal Signal Strength. - Shirshendu Chatterjee; Soumendu Sundar Mukherjee; Tamojit Sadhukhan (AISTATS, 2025)

Optimal Transfer Learning for Missing Not-at-Random Matrix Completion. - Akhil Jalan; Yassir Jedra; Arya Mazumdar; Soumendu Sundar Mukherjee; Purnamrita Sarkar (CoRR, 2025)

Learning under Latent Group Sparsity via Diffusion on Networks. - Subhroshekhar Ghosh; Soumendu Sundar Mukherjee (CoRR, 2025)