Rajdip Nayek

1. Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations
   2024/04/24 by Sawan Kumar, Kumar, Sawan, Rajdip Nayek +3 · 2 citations
   Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Target Tracking and Data Fusion in Sensor Networks
2. Discovering stochastic partial differential equations from limited data using variational Bayes inference
   2023/06/28 by Yogesh Chandrakant Mathpati, Tapas Tripura, Mathpati, Yogesh Chandrakant +5 · 1 citation
   Computer Science · Engineering · Environmental Science · #Energy Load and Power Forecasting #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Hydrological Forecasting Using AI #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Towards Gaussian Process for operator learning: an uncertainty aware resolution independent operator learning algorithm for computational mechanics
   2024/09/17 by Sawan Kumar, Kumar, Sawan, Rajdip Nayek +3 · 2 citations
   Computer Science · Engineering · Physics and Astronomy · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks