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2410.13141
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Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity
17 October 2024
Handi Zhang
Langchen Liu
Lu Lu
FedML
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Papers citing
"Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity"
17 / 17 papers shown
Title
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
Zhongkai Hao
J. Yao
Chang Su
Hang Su
Ziao Wang
...
Zeyu Xia
Yichi Zhang
Songming Liu
Lu Lu
Jun Zhu
PINN
88
32
0
15 Jun 2023
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks
Chen-Chun Wu
Min Zhu
Qinyan Tan
Yadhu Kartha
Lu Lu
86
375
0
21 Jul 2022
MIONet: Learning multiple-input operators via tensor product
Pengzhan Jin
Shuai Meng
Lu Lu
67
171
0
12 Feb 2022
Parallel Physics-Informed Neural Networks via Domain Decomposition
K. Shukla
Ameya Dilip Jagtap
George Karniadakis
PINN
162
284
0
20 Apr 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Sizhuang He
Hanwen Wang
P. Perdikaris
AI4CE
97
699
0
19 Mar 2021
Physics-informed neural networks with hard constraints for inverse design
Lu Lu
R. Pestourie
Wenjie Yao
Zhicheng Wang
F. Verdugo
Steven G. Johnson
PINN
97
517
0
09 Feb 2021
Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications
David Byrd
Antigoni Polychroniadou
FedML
49
156
0
12 Oct 2020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
L. McClenny
U. Braga-Neto
PINN
80
459
0
07 Sep 2020
Adaptive Federated Optimization
Sashank J. Reddi
Zachary B. Charles
Manzil Zaheer
Zachary Garrett
Keith Rush
Jakub Konecný
Sanjiv Kumar
H. B. McMahan
FedML
177
1,437
0
29 Feb 2020
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedML
AI4CE
259
6,261
0
10 Dec 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
Kang Wei
Jun Li
Ming Ding
Chuan Ma
Heng Yang
Farokhi Farhad
Shi Jin
Tony Q.S. Quek
H. Vincent Poor
FedML
125
1,616
0
01 Nov 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Lu Lu
Pengzhan Jin
George Karniadakis
248
2,131
0
08 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
T. Hsu
Qi
Matthew Brown
FedML
143
1,150
0
13 Sep 2019
DeepXDE: A deep learning library for solving differential equations
Lu Lu
Xuhui Meng
Zhiping Mao
George Karniadakis
PINN
AI4CE
97
1,533
0
10 Jul 2019
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
Li Huang
Dianbo Liu
OOD
FedML
71
368
0
22 Mar 2019
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
406
17,486
0
17 Feb 2016
Cases for the nugget in modeling computer experiments
R. Gramacy
Herbert K. H. Lee
140
280
0
26 Jul 2010
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