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07/23/2023
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks
The curse-of-dimensionality (CoD) taxes computational resources heavily ...
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03/01/2023
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
Kohn-Sham Density Functional Theory (KS-DFT) has been traditionally solv...
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11/16/2022
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology
In this paper, we propose the augmented physics-informed neural network ...
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07/19/2022
Enhancing Collaborative Filtering Recommender with Prompt-Based Sentiment Analysis
Collaborative Filtering(CF) recommender is a crucial application in the ...
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10/24/2021
Kernelized Heterogeneous Risk Minimization
The ability to generalize under distributional shifts is essential to re...
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09/20/2021
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?
Physics-informed neural networks (PINNs) have become a popular choice fo...
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05/09/2021
Heterogeneous Risk Minimization
Machine learning algorithms with empirical risk minimization usually suf...
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07/07/2020
