- π PhD Candidate @Tu Delft
- π» Working: Bayesian machine learning, multi-fidelity modeling/optimization, and multi-scale simulation
- πͺ Learning: Be an independent researcher
- π± Hobbies: βΉοΈββοΈ πββοΈ πββοΈ πΈ π§βπ³ π₯’
- π¬ Personal website
Hi, there! Here is Jiaxiang, a PhD candidate at 3mE-MSE of TU Delft. I am working on bayesian machine learning and optimization
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Delft University of Technology
- Delft, the Netherlands
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16:38
(UTC +02:00) - JiaxiangYi96.github.io
Highlights
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AMK-MCS-AEFF
AMK-MCS-AEFF Publican active-learning method for reliability analysis based on multi-fidelity kriging model
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bessagroup/rvesimulator
bessagroup/rvesimulator PublicAutomated representative volume element simulator via abaqus for material constitutive law discovery
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bessagroup/MF-VeBRNN
bessagroup/MF-VeBRNN PublicSingle-to-multi-fidelity bayesian reccurent neural network for learning path dependent constitutive law
Jupyter Notebook 5
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bessagroup/VeBNN
bessagroup/VeBNN PublicCooperative variance estimation and Bayesian neural networks disentangle aleatoric and epistemic uncertainties
Jupyter Notebook 3
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