10 papers
ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces
Kunal Kumar Pant, Nithin Nagaraj
Transformer models are most often understood through what they do: their benchmark performance, generation quality, or behavior on downstream tasks. Yet frozen transformer input-em…
Benchmarking ConvLSTM for One-Day-Ahead IMDAA Rainfall-Field Prediction across Four Indian Cities
Tanmay Ghosh, Shaurabh Anand, Rakesh Gomaji Nannewar +1
Convolutional long short-term memory networks (ConvLSTMs) are widely used for precipitation forecasting, but most evidence for their performance comes from dense, high-frequency ra…
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…
Linked Data Classification using Neurochaos Learning
Pooja Honna, Ayush Patravali, Nithin Nagaraj +1
Neurochaos Learning (NL) has shown promise in recent times over traditional deep learning due to its two key features: ability to learn from small sized training samples, and low c…
Dependable Artificial Intelligence with Reliability and Security (DAIReS): A Unified Syndrome Decoding Approach for Hallucination and Backdoor Trigger Detection
Hema Karnam Surendrababu, Nithin Nagaraj
Machine Learning (ML) models, including Large Language Models (LLMs), are characterized by a range of system-level attributes such as security and reliability. Recent studies have…
Advancing Forest Fires Classification using Neurochaos Learning
Kunal Kumar Pant, Remya Ajai A S, Nithin Nagaraj
Forest fires are among the most dangerous and unpredictable natural disasters worldwide. Forest fire can be instigated by natural causes or by humans. They are devastating overall,…
Hyperparameter-Free Neurochaos Learning Algorithm for Classification
Akhila Henry, Nithin Nagaraj
Neurochaos Learning (NL) is a brain-inspired classification framework that employs chaotic dynamics to extract features from input data and yields state of the art performance on c…
Augmented Regression Models using Neurochaos Learning
Akhila Henry, Nithin Nagaraj
This study presents novel Augmented Regression Models using Neurochaos Learning (NL), where Tracemean features derived from the Neurochaos Learning framework are integrated with tr…
A Chaos Driven Metric for Backdoor Attack Detection
Hema Karnam Surendrababu, Nithin Nagaraj
The advancement and adoption of Artificial Intelligence (AI) models across diverse domains have transformed the way we interact with technology. However, it is essential to recogni…
Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda
Nanjangud C. Narendra, Nithin Nagaraj
Deep learning implemented via neural networks, has revolutionized machine learning by providing methods for complex tasks such as object detection/classification and prediction. Ho…