Rahul Biswas

Alumni


Graduated in 2023
ORCID iD  0000-0002-3579-4790 

Preprints

Tensor Recovery in High-Dimensional Ising Models
Tianyu Liu, Somabha Mukherjee, Rahul Biswas
The $k$-tensor Ising model is an exponential family on a $p$-dimensional binary hypercube for modeling dependent binary data, where the sufficient statistic…

Application of Time-Aware PC algorithm to compute Causal Functional Connectivity in Alzheimer's Disease from fMRI data
Rahul Biswas, SuryaNarayana Sripada
Functional Connectivity between brain regions is known to be altered in Alzheimer's disease, and promises to be a biomarker for early diagnosis of the disease…

Inferring Causality from Time Series data based on Structural Causal Model and its application to Neural Connectomics
Rahul Biswas, SuryaNarayana Sripada, Somabha Mukherjee
Inferring causation from time series data is of scientific interest in different disciplines, particularly in neural connectomics. While different approaches…

Statistical Perspective on Functional and Causal Neural Connectomics: The Time-Aware PC Algorithm
Rahul Biswas, Eli Shlizerman
The representation of the flow of information between neurons in the brain based on their activity is termed the causal functional connectome. Such…

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…

Statistical Perspective on Functional and Causal Neural Connectomics: A Comparative Study
Rahul Biswas, Eli Shlizerman
Representation of brain network interactions is fundamental to the translation of neural structure to brain function. As such, methodologies for mapping neural…

Neuro-PC: Causal Functional Connectivity from Neural Dynamics
Rahul Biswas, Eli Shlizerman
Functional connectome extends the anatomical connectome by capturing the relations between neurons according to their activity and interactions. When these…

On high-dimensional modifications of some graph-based two-sample tests
Soham Sarkar, Rahul Biswas, Anil K. Ghosh
Testing for the equality of two high-dimensional distributions is a challenging problem, and this becomes even more challenging when the sample size is small…

A Peak Synchronization Measure for Multiple Signals
Rahul Biswas, Koulik Khamaru, Kaushik Majumdar
Peaks signify important events in a signal. In a pair of signals how peaks are occurring with mutual correspondence may offer us significant insights into the…