14 citations · 33 across the 24 of their papers we have counts for
29 papers
Scaling Limits for Ising Models on Inhomogeneous Random Graphs and Applications
Sanchayan Bhowal, Anirban Chatterjee, Somabha Mukherjee
In this paper, we derive quenched scaling limits for linear functionals and the empirical spin field of Ising models on inhomogeneous random graphs generated by a graphon (encompas…
Ising Models on Inhomogeneous Random Graphs: Inference, Local Asymptotic Minimaxity, and Limit of Experiments
Somabha Mukherjee, Sanchayan Bhowal, Anirban Chatterjee +1
In this paper, we develop an inferential framework with sharp asymptotic optimality guarantees for Ising models on inhomogeneous random graphs in the subcritical parameter regime.…
Joint Estimation in Potts Model
Somabha Mukherjee, Sumit Mukherjee, Sayar Karmakar
In this paper, we study estimation of parameters in a two-parameter Potts model with colors and coupling matrix . We characterize concrete sufficient conditions for existe…
Robust Estimation for Dependent Binary Network Data
Tianyu Liu, Somabha Mukherjee, Abhik Ghosh
We consider the problem of learning the interaction strength between the nodes of a network based on dependent binary observations residing on these nodes, generated from a Markov…
Mixing Phases and Metastability for the Glauber Dynamics on the p-Spin Curie-Weiss Model
Ramkrishna Jyoti Samanta, Somabha Mukherjee, Jiang Zhang
The Glauber dynamics for the classical -spin Curie-Weiss model on nodes with inverse temperature and zero external field is known to mix in time for $β< \fr…
Interaction Order Estimation in Tensor Curie-Weiss Models
Somabha Mukherjee
In this paper, we consider the problem of estimating the interaction parameter of a -spin Curie-Weiss model at inverse temperature , given a single observation from this…
Rates of Convergence of the Magnetization in the Tensor Curie-Weiss Potts Model
Sanchayan Bhowal, Somabha Mukherjee
In this paper, we derive distributional convergence rates for the magnetization vector and the maximum pseudolikelihood estimator of the inverse temperature parameter in the tensor…
Moderate Deviation and Berry-Esseen Bounds in the -Spin Curie-Weiss Model
Somabha Mukherjee, Tianyu Liu, Bhaswar B. Bhattacharya
Limit theorems for the magnetization in the -spin Curie-Weiss model, for , has been derived recently by Mukherjee et al. (2021). In this paper, we strengthen these res…
Optimal Confidence Bands for Shape-restricted Regression in Multidimensions
Ashley, Datta, Somabha Mukherjee +1
In this paper, we propose and study construction of confidence bands for shape-constrained regression functions when the predictor is multivariate. In particular, we consider the c…
Interaction Screening and Pseudolikelihood Approaches for Tensor Learning in Ising Models
Tianyu Liu, Somabha Mukherjee
In this paper, we study two well known methods of Ising structure learning, namely the pseudolikelihood approach and the interaction screening approach, in the context of tensor re…
Limit Theorems and Phase Transitions in the Tensor Curie-Weiss Potts Model
Sanchayan Bhowal, Somabha Mukherjee
In this paper, we derive results about the limiting distribution of the empirical magnetization vector and the maximum likelihood (ML) estimates of the natural parameters in the te…
Tensor Recovery in High-Dimensional Ising Models
Tianyu Liu, Somabha Mukherjee, Rahul Biswas
The -tensor Ising model is an exponential family on a -dimensional binary hypercube for modeling dependent binary data, where the sufficient statistic consists of all -fol…
Consistent Causal Inference from Time Series with PC Algorithm and its Time-Aware Extension
Rahul Biswas, Somabha Mukherjee
The estimator of a causal directed acyclic graph (DAG) with the PC algorithm is known to be consistent based on independent and identically distributed samples. In this paper, we c…
Fluctuations of Quadratic Chaos
Bhaswar B. Bhattacharya, Sayan Das, Somabha Mukherjee +1
In this paper we characterize all distributional limits of the random quadratic form , where is a $\{0,…
High Dimensional Logistic Regression Under Network Dependence
Somabha Mukherjee, Ziang Niu, Sagnik Halder +2
Logistic regression is key method for modeling the probability of a binary outcome based on a collection of covariates. However, the classical formulation of logistic regression re…
Limit theorems for dependent combinatorial data, with applications in statistical inference
Somabha Mukherjee
The Ising model is a celebrated example of a Markov random field, introduced in statistical physics to model ferromagnetism. This is a discrete exponential family with binary outco…
Efficient Estimation in Tensor Ising Models
Somabha Mukherjee, Jaesung Son, Swarnadip Ghosh +1
The tensor Ising model is a discrete exponential family used for modeling binary data on networks with not just pairwise, but higher-order dependencies. A particularly important cl…
Feature Selection in High-dimensional Spaces Using Graph-Based Methods
Swarnadip Ghosh, Somabha Mukherjee, Divyansh Agarwal +3
High-dimensional feature selection is a central problem in a variety of application domains such as machine learning, image analysis, and genomics. In this paper, we propose graph-…
Estimation in Tensor Ising Models
Somabha Mukherjee, Jaesung Son, Bhaswar B. Bhattacharya
The -tensor Ising model is a one-parameter discrete exponential family for modeling dependent binary data, where the sufficient statistic is a multi-linear form of degree $p \ge…
Phase Transitions of the Maximum Likelihood Estimates in the -Spin Curie-Weiss Model
Somabha Mukherjee, Jaesung Son, Bhaswar B. Bhattacharya
In this paper we consider the problem of parameter estimation in the -spin Curie-Weiss model, for . We provide a complete description of the limiting properties of the…
Asymptotic bounds on graphical partitions and partition comparability
Stephen Melczer, Marcus Michelen, Somabha Mukherjee
An integer partition is called graphical if it is the degree sequence of a simple graph. We prove that the probability that a uniformly chosen partition of size is graphical de…
Least Squares Estimation of a Quasiconvex Regression Function
Somabha Mukherjee, Rohit K. Patra, Andrew L. Johnson +1
We develop a new approach for the estimation of a multivariate function based on the economic axioms of quasiconvexity (and monotonicity). On the computational side, we prove the e…
Asymptotic Distribution of Bernoulli Quadratic Forms
Bhaswar B. Bhattacharya, Somabha Mukherjee, Sumit Mukherjee
Consider the random quadratic form , where is a -valued symmetric matrix with zeros on th…
Distribution-Free Multisample Test Based on Optimal Matching with Applications to Single Cell Genomics
Divyansh Agarwal, Somabha Mukherjee, Bhaswar Bikram Bhattacharya +1
In this paper we propose a nonparametric graphical test based on optimal matching, for assessing the equality of multiple unknown multivariate probability distributions. Our proced…