Piyush Pandita

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 16

Top Topics

Gaussian Process

Top Venues

J. Comput. Inf. Sci. Eng.

AAAI Spring Symposium: MLPS

Publications

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
Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process. CoRR (2024)
Yigitcan Comlek, Sandipp Krishnan Ravi, Piyush Pandita, Sayan Ghosh, Liping Wang, Wei Chen
Heterogenous Multi-Source Data Fusion Through Input Mapping and Latent Variable Gaussian Process. CoRR (2024)
Anindya Bhaduri, Nesar Ramachandra, Sandipp Krishnan Ravi, Lele Luan, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang
Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data. J. Comput. Inf. Sci. Eng. 24 (4) (2024)
Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi, Anindya Bhaduri, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field. CoRR (2023)
Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Liping Wang
Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds. Entropy 24 (9) (2022)
Yuhao Wang, Yi Gao, Yongming Liu, Sayan Ghosh, Waad Subber, Piyush Pandita, Liping Wang
Bayesian-entropy gaussian process for constrained metamodeling. Reliab. Eng. Syst. Saf. 214 (2021)
Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem
Data-based Discovery of Governing Equations. AAAI Spring Symposium: MLPS (2021)
Yonatan Ashenafi, Piyush Pandita, Sayan Ghosh
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design. CoRR (2021)
Sayan Ghosh, Govinda A. Padmanabha, Cheng Peng, Steven Atkinson, Valeria Andreoli, Piyush Pandita, Thomas Vandeputte, Nicholas Zabaras, Liping Wang
Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning. CoRR (2021)
Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Valeria Andreoli, Thomas Vandeputte, Liping Wang
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes. CoRR (2020)
Raphael Gautier, Piyush Pandita, Sayan Ghosh, Dimitri Mavris
A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes. CoRR (2020)
Sayan Ghosh, Piyush Pandita, Steven Atkinson, Waad Subber, Yiming Zhang, Natarajan Chennimalai-Kumar, Suryarghya Chakrabarti, Liping Wang
Advances in Bayesian Probabilistic Modeling for Industrial Applications. CoRR (2020)
Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem
Data-based Discovery of Governing Equations. CoRR (2020)
Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis, Jitesh H. Panchal
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design. CoRR (2019)
Piyush Pandita, Jesper Kristensen, Liping Wang
Towards Scalable Gaussian Process Modeling. CoRR (2019)
Piyush Pandita, Ilias Bilionis, Jitesh H. Panchal
Deriving Information Acquisition Criteria For Sequentially Inferring The Expected Value Of A Black-Box Function. CoRR (2018)