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A non-cooperative meta-modeling game for automated third-party
  calibrating, validating, and falsifying constitutive laws with parallelized
  adversarial attacks

A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks

13 April 2020
Kun Wang
WaiChing Sun
Q. Du
ArXivPDFHTML

Papers citing "A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks"

4 / 4 papers shown
Title
Physics-Informed Deep Learning For Traffic State Estimation: A Survey
  and the Outlook
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook
Xuan Di
Rongye Shi
Zhaobin Mo
Yongjie Fu
PINN
AI4TS
AI4CE
24
28
0
03 Mar 2023
Design of experiments for the calibration of history-dependent models
  via deep reinforcement learning and an enhanced Kalman filter
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter
Ruben Villarreal
Nikolaos N. Vlassis
Nhon N. Phan
Tommie A. Catanach
Reese E. Jones
N. Trask
S. Kramer
WaiChing Sun
OffRL
14
11
0
27 Sep 2022
Geometric deep learning for computational mechanics Part II: Graph
  embedding for interpretable multiscale plasticity
Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity
Nikolaos N. Vlassis
WaiChing Sun
AI4CE
6
32
0
30 Jul 2022
Sobolev training of thermodynamic-informed neural networks for smoothed
  elasto-plasticity models with level set hardening
Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening
Nikolaos N. Vlassis
WaiChing Sun
AI4CE
6
2
0
15 Oct 2020
1