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cs.LG2025
Event-driven physics-informed operator learning for reliability analysis
Shailesh Garg, Souvik Chakraborty
Reliability analysis of engineering systems under uncertainty poses significant computational challenges, particularly for problems involving high-dimensional stochastic inputs, no…
physics.comp-ph2025
NeuroPINNs: Neuroscience Inspired Physics Informed Neural Networks
Shailesh Garg, Souvik Chakraborty
We introduce NeuroPINNs, a neuroscience-inspired extension of Physics-Informed Neural Networks (PINNs) that incorporates biologically motivated spiking neuron models to achieve ene…
cs.LG2025
Competition is the key: A Game Theoretic Causal Discovery Approach
Amartya Roy, Souvik Chakraborty
Causal discovery remains a central challenge in machine learning, yet existing methods face a fundamental gap: algorithms like GES and GraN-DAG achieve strong empirical performance…