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Physics Informed Deep Kernel Learning
v1v2 (latest)

Physics Informed Deep Kernel Learning

8 June 2020
Liang Luo
Wei W. Xing
Robert M. Kirby
Shandian Zhe
    PINN
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Papers citing "Physics Informed Deep Kernel Learning"

4 / 4 papers shown
Response to Promises and Pitfalls of Deep Kernel Learning
Response to Promises and Pitfalls of Deep Kernel Learning
A. Wilson
Zhiting Hu
Ruslan Salakhutdinov
Eric P. Xing
UQCV
200
0
0
25 Sep 2025
Knowledge-augmented Deep Learning and Its Applications: A Survey
Knowledge-augmented Deep Learning and Its Applications: A SurveyIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Zijun Cui
Tian Gao
Kartik Talamadupula
Qiang Ji
337
43
0
30 Nov 2022
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes:
  Covariance, Expressivity, and Neural Tangent Kernel
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel
Chi-Ken Lu
Patrick Shafto
BDL
388
1
0
14 Mar 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
AutoIP: A United Framework to Integrate Physics into Gaussian ProcessesInternational Conference on Machine Learning (ICML), 2022
D. Long
Liang Luo
Aditi S. Krishnapriyan
Robert M. Kirby
Shandian Zhe
Michael W. Mahoney
AI4CE
411
23
0
24 Feb 2022
1
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