Multivariate CLT follows from strong Rayleigh property. - Subhroshekhar Ghosh; Thomas M. Liggett; Robin Pemantle (ANALCO, 2017)

Learning from DPPs via Sampling: Beyond HKPV and symmetry. - Rémi Bardenet; Subhroshekhar Ghosh (CoRR, 2020)

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. - Zhaoqiang Liu; Subhroshekhar Ghosh; Jonathan Scarlett (ITW, 2021)

Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD. - Rémi Bardenet; Subhroshekhar Ghosh; Meixia Lin (NeurIPS, 2021)

Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors. - Zhaoqiang Liu; Subhroshekhar Ghosh; Jonathan Scarlett (NeurIPS, 2021)

Estimation and inference of signals via the stochastic geometry of spectrogram level sets. - Subhroshekhar Ghosh; Meixia Lin; Dongfang Sun (CoRR, 2021)

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. - Zhaoqiang Liu; Subhroshekhar Ghosh; Jun Han; Jonathan Scarlett (CoRR, 2021)

Generative Principal Component Analysis. - Zhaoqiang Liu; Jiulong Liu; Subhroshekhar Ghosh; Jun Han; Jonathan Scarlett (ICLR, 2022)

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

Fractal Gaussian Networks: A Sparse Random Graph Model Based on Gaussian Multiplicative Chaos. - Subhroshekhar Ghosh; Krishnakumar Balasubramanian 002; Xiaochuan Yang (IEEE Trans. Inf. Theory, 2022)

Disordered Complex Networks: Energy Optimal Lattices and Persistent Homology. - Subhroshekhar Ghosh; Naoto Miyoshi; Tomoyuki Shirai (IEEE Trans. Inf. Theory, 2022)

Signal Analysis via the Stochastic Geometry of Spectrogram Level Sets. - Subhroshekhar Ghosh; Meixia Lin; Dongfang Sun (IEEE Trans. Signal Process., 2022)

Dictionary Learning under Symmetries via Group Representations. - Subhroshekhar Ghosh; Aaron Y. R. Low; Yong Sheng Soh; Zhuohang Feng; Brendan K. Y. Tan (CoRR, 2023)

Sparse Multi-Reference Alignment: Phase Retrieval, Uniform Uncertainty Principles and the Beltway Problem. - Subhroshekhar Ghosh; Philippe Rigollet (Found. Comput. Math., 2023)

Maximum Likelihood Estimation Under Constraints: Singularities and Random Critical Points. - Subhroshekhar Ghosh; Sanjay Chaudhuri; Ujan Gangopadhyay (IEEE Trans. Inf. Theory, 2023)

Small coresets via negative dependence: DPPs, linear statistics, and concentration. - Rémi Bardenet; Subhroshekhar Ghosh; Hugo Simon-Onfroy; Hoang Son Tran (NeurIPS, 2024)

On an Empirical Likelihood Based Solution to the Approximate Bayesian Computation Problem. - Sanjay Chaudhuri; Subhroshekhar Ghosh; Kim Cuc Pham (Stat. Anal. Data Min., 2024)

Negative Dependence as a toolbox for machine learning : review and new developments. - Hoang Son Tran; Vladimir Petrovic; Rémi Bardenet; Subhroshekhar Ghosh (CoRR, 2025)

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