Data based intervention approach for Complexity-Causality measure. - Aditi Kathpalia; Nithin Nagaraj (PeerJ Prepr., 2018)

A novel compression based neuronal architecture for memory encoding. - Aditi Kathpalia; Nithin Nagaraj (ICDCN, 2019)

ChaosNet: A Chaos based Artificial Neural Network Architecture for Classification. - Harikrishnan Nellippallil Balakrishnan; Aditi Kathpalia; Snehanshu Saha; Nithin Nagaraj (CoRR, 2019)

Learning Generalized Causal Structure in Time-series. - Aditi Kathpalia; Keerti P. Charantimath; Nithin Nagaraj (CoRR, 2021)

Time-Reversibility, Causality and Compression-Complexity. - Aditi Kathpalia; Nithin Nagaraj (Entropy, 2021)

Causality Preserving Chaotic Transformation and Classification using Neurochaos Learning. - Harikrishnan N. B.; Aditi Kathpalia; Nithin Nagaraj (NeurIPS, 2022)

Cause-Effect Preservation and Classification using Neurochaos Learning. - Harikrishnan N. B.; Aditi Kathpalia; Nithin Nagaraj (CoRR, 2022)

Granger Causality for Compressively Sensed Sparse Signals. - Aditi Kathpalia; Nithin Nagaraj (CoRR, 2022)

Compression Spectrum: Where Shannon meets Fourier. - Aditi Kathpalia; Nithin Nagaraj (CoRR, 2023)

Response prediction of antidepressants: Using graph theory tools for brain network connectivity analysis. - Akbar Davoodi; Martin Holena; Martin Brunovsky; Aditi Kathpalia; Jaroslav Hlinka; Martin Bares; Milan Palus (Biomed. Signal Process. Control., 2025)