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Piyush Pandita
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2020 – today
- 2024
- [j3]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) - [i12]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 abs/2402.04146 (2024) - [i11]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 abs/2407.11268 (2024) - 2023
- [i10]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 abs/2303.16869 (2023) - 2022
- [j2]Panagiotis Tsilifis
Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds. Entropy 24(9): 1291 (2022) - 2021
- [j1]Yuhao Wang
Bayesian-entropy gaussian process for constrained metamodeling. Reliab. Eng. Syst. Saf. 214: 107762 (2021) - [c1]Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem:
Data-based Discovery of Governing Equations. AAAI Spring Symposium: MLPS 2021 - [i9]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 abs/2108.10163 (2021) - [i8]Yonatan Ashenafi, Piyush Pandita, Sayan Ghosh:
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design. CoRR abs/2112.10944 (2021) - 2020
- [i7]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 abs/2003.11939 (2020) - [i6]Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Valeria Andreoli, Thomas Vandeputte, Liping Wang:
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes. CoRR abs/2008.02386 (2020) - [i5]Raphael Gautier, Piyush Pandita, Sayan Ghosh, Dimitri Mavris:
A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes. CoRR abs/2008.03534 (2020) - [i4]Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem:
Data-based Discovery of Governing Equations. CoRR abs/2012.06036 (2020)
2010 – 2019
- 2019
- [i3]Piyush Pandita, Jesper Kristensen, Liping Wang:
Towards Scalable Gaussian Process Modeling. CoRR abs/1907.11313 (2019) - [i2]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 abs/1912.07366 (2019) - 2018
- [i1]Piyush Pandita, Ilias Bilionis, Jitesh H. Panchal:
Deriving Information Acquisition Criteria For Sequentially Inferring The Expected Value Of A Black-Box Function. CoRR abs/1807.09979 (2018)
Coauthor Index
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