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09/20/2023
Compression Spectrum: Where Shannon meets Fourier
Signal processing and Information theory are two disparate fields used f...
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08/19/2023
To prune or not to prune : A chaos-causality approach to principled pruning of dense neural networks
Reducing the size of a neural network (pruning) by removing weights with...
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07/05/2023
Kolam Simulation using Angles at Lattice Points
Kolam is a ritual art form practised by people in South India and consis...
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06/05/2023
Permutation Decision Trees
Decision Tree is a well understood Machine Learning model that is based ...
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09/23/2022
Granger Causality for Compressively Sensed Sparse Signals
Compressed sensing is a scheme that allows for sparse signals to be acqu...
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04/20/2022
Neurochaos Feature Transformation and Classification for Imbalanced Learning
Learning from limited and imbalanced data is a challenging problem in th...
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01/28/2022
Cause-Effect Preservation and Classification using Neurochaos Learning
Discovering cause-effect from observational data is an important but cha...
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12/06/2021
Learning Generalized Causal Structure in Time-series
The science of causality explains/determines 'cause-effect' relationship...
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10/24/2021
Problems with information theoretic approaches to causal learning
The language of information theory is favored in both causal reasoning a...
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09/24/2021
Causal Analysis of Carnatic Music: A Preliminary Study
The musicological analysis of Carnatic music is challenging, owing to it...
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02/02/2021
When Noise meets Chaos: Stochastic Resonance in Neurochaos Learning
Chaos and Noise are ubiquitous in the Brain. Inspired by the chaotic fir...
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10/19/2020
Causal Discovery using Compression-Complexity Measures
Causal inference is one of the most fundamental problems across all doma...
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10/12/2020
A Neurochaos Learning Architecture for Genome Classification
There has been empirical evidence of presence of non-linearity and chaos...
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10/19/2019
Measuring Causality: The Science of Cause and Effect
Determining and measuring cause-effect relationships is fundamental to m...
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10/06/2019
ChaosNet: A Chaos based Artificial Neural Network Architecture for Classification
Inspired by chaotic firing of neurons in the brain, we propose ChaosNet ...
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06/01/2019
Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets
We present analytical exploration of novel activation functions as conse...
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05/19/2019