124 citations · 190 across the 14 of their papers we have counts for
4 papers · 1 filter
Probabilistic Digital Twin for Misspecified Structural Dynamical Systems via Latent Force Modeling and Bayesian Neural Networks
Sahil Kashyap, Rajdip Nayek
This work presents a probabilistic digital twin framework for response prediction in dynamical systems governed by misspecified physics. The approach integrates Gaussian Process La…
Safe Reinforcement Learning-Based Vibration Control: Overcoming Training Risks with LQR Guidance
Rohan Vitthal Thorat, Juhi Singh, Rajdip Nayek
Structural vibrations induced by external excitations pose significant risks, including safety hazards for occupants, structural damage, and increased maintenance costs. While conv…
From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems
Sawan Kumar, Tapas Tripura, Rajdip Nayek +1
Operator learning offers a powerful paradigm for solving parametric partial differential equations (PDEs), but scaling probabilistic neural operators such as the recently proposed…
A recursive Bayesian neural network for constitutive modeling of sands under monotonic and cyclic loading
Toiba Noor, Soban Nasir Lone, G. V. Ramana +1
In geotechnical engineering, constitutive models are central to capturing soil behavior across diverse drainage conditions, stress paths,and loading histories. While data driven de…