cics-nd Goto Github PK
Name: Center for Informatics and Computational Science
Type: Organization
Center for Informatics and Computational Science's Projects
ar-pde-cnn
Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
caae-drdcn-inverse
Deep residual networks for dimensionality reduction and surrogate modeling in high-dimensional inverse problems
cnn-inversion
Deep autoregressive neural networks for high-dimensional inverse problems
cnn-surrogate
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
dcedn-gcs
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multi-phase flow in heterogeneous random media
gptorch
Gaussian processes with PyTorch
pde-surrogate
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
predictive-cvs
Predictive collective variable discovery with deep Bayesian models for atomistic systems.
rans-uncertainty
Uncertainty Quantification of RANS Data-Driven Turbulence Modeling
sgp-experiments
Experiments using the structured GP, GP-LVM, and warped GP.
sgplvm-inverse
Experiments using the structured Bayesian Gaussian process latent variable model for inverse problems
structured-gpflow
Gaussian process models with structured inputs based on GPflow
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