Piyush Pandita

According to our database, Piyush Pandita authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process.

Sandipp Krishnan Ravi, Yigitcan Comlek, Wei Chen, Arjun Pathak, Vipul Gupta, Rajnikant Umretiya, Andrew Hoffman, Ghanshyam Pilania, Piyush Pandita, Sayan Ghosh, Nathaniel Mckeever, Liping Wang

CoRR, 2024

2023

Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field.

Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi, Anindya Bhaduri, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang

CoRR, 2023

2022

Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds.

Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Liping Wang

Entropy, 2022

2021

Bayesian-entropy gaussian process for constrained metamodeling.

Yuhao Wang, Yi Gao, Yongming Liu, Sayan Ghosh, Waad Subber, Piyush Pandita, Liping Wang

Reliab. Eng. Syst. Saf., 2021

Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design.

Yonatan Ashenafi, Piyush Pandita, Sayan Ghosh

CoRR, 2021

Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning.

Sayan Ghosh, Govinda A. Padmanabha, Cheng Peng, Steven Atkinson, Valeria Andreoli, Piyush Pandita, Thomas Vandeputte, Nicholas Zabaras, Liping Wang

CoRR, 2021

Data-based Discovery of Governing Equations.

Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2020

A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes.

Raphael Gautier, Piyush Pandita, Sayan Ghosh, Dimitri Mavris

CoRR, 2020

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes.

Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Valeria Andreoli, Thomas Vandeputte, Liping Wang

CoRR, 2020

Advances in Bayesian Probabilistic Modeling for Industrial Applications.

Sayan Ghosh, Piyush Pandita, Steven Atkinson, Waad Subber, Yiming Zhang, Natarajan Chennimalai-Kumar, Suryarghya Chakrabarti, Liping Wang

CoRR, 2020

2019

Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design.

Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis, Jitesh H. Panchal

CoRR, 2019

Towards Scalable Gaussian Process Modeling.

Piyush Pandita, Jesper Kristensen, Liping Wang

CoRR, 2019

2018

Deriving Information Acquisition Criteria For Sequentially Inferring The Expected Value Of A Black-Box Function.

Piyush Pandita, Ilias Bilionis, Jitesh H. Panchal

CoRR, 2018