K. Chowdappa

Efficient Posterior Approximation for Bayesian Neural Networks in Large-Scale Distributed Environments

Bayesian neural networks (BNNs) introduce a principled framework for uncertainty estimation through learning probability distributions with respect to model parameters. Still, current deep networks are not only unfeasible to perform exact Bayesian inference, but traditional posterior approximation methods also incur si...

COGNIA: A Cognitive Collaboration Framework for Adaptive Decision-Making in Autonomous Embodied Intelligence

Autonomous embodied intelligence has emerged as a promising new paradigm to enable intelligent agents to perceive, reason, and interact with dynamic environments. Recent advances in large language models (LLMs), vision-language models, and multi-agent systems have greatly improved embodied decision-making. But many cur...

Autonomous Digital Twin Framework for Predictive Cyber Defense in Edge-IoT Networks