12 citations · 12 across the 4 of their papers we have counts for
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cs.LG2021★ 12 cited
Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks
Xiang Huang, Hongsheng Liu, Beiji Shi +11
In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs) emerges to be a pro…
cs.LG2020
Interpretable Models in ANNs
Yang Li
Artificial neural networks are often very complex and too deep for a human to understand. As a result, they are usually referred to as black boxes. For a lot of real-world problems…
cs.LG2019
Inferring Latent dimension of Linear Dynamical System with Minimum Description Length
Yang Li
Time-invariant linear dynamical system arises in many real-world applications,and its usefulness is widely acknowledged. A practical limitation with this model is that its latent d…