activity
20192026
most citedMeasuring Causality: The Science of Cause and Effect

2 citations · 4 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ML2026

Dictionary Based Pattern Entropy for Causal Direction Discovery

Harikrishnan N B, Shubham Bhilare, Aditi Kathpalia +1

Discovering causal direction from temporal observational data is particularly challenging for symbolic sequences, where functional models and noise assumptions are often unavailabl…

cs.IT2023

Compression Spectrum: Where Shannon meets Fourier

Aditi Kathpalia, Nithin Nagaraj

Signal processing and Information theory are two disparate fields used for characterizing signals for various scientific and engineering applications. Spectral/Fourier analysis, a…

cs.LG20221 cited

Cause-Effect Preservation and Classification using Neurochaos Learning

Harikrishnan N B, Aditi Kathpalia, Nithin Nagaraj

Discovering cause-effect from observational data is an important but challenging problem in science and engineering. In this work, a recently proposed brain inspired learning algor…

stat.ME20192 cited

Measuring Causality: The Science of Cause and Effect

Aditi Kathpalia, Nithin Nagaraj

Determining and measuring cause-effect relationships is fundamental to most scientific studies of natural phenomena. The notion of causation is distinctly different from correlatio…

cs.LG20191 cited

ChaosNet: A Chaos based Artificial Neural Network Architecture for Classification

Harikrishnan Nellippallil Balakrishnan, Aditi Kathpalia, Snehanshu Saha +1

Inspired by chaotic firing of neurons in the brain, we propose ChaosNet -- a novel chaos based artificial neural network architecture for classification tasks. ChaosNet is built us…

math.DS2019

Causal Stability and Synchronization

Aditi Kathpalia, Nithin Nagaraj

Synchronization of chaos arises between coupled dynamical systems and is very well understood as a temporal phenomena which leads the coupled systems to converge or develop a depen…