58:49
Youngsoo Choi: Efficient physics-constrained data-driven physical simulations
Machine Learning and Dynamical Systems Seminar
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1:07:31
DDPS | libROM: Library for physics-constrained data-driven physical simulations | Youngsoo Choi
Inside Livermore Lab
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1:03:50
AJS - Youngsoo Choi - Where are we with data-driven surrogate modeling for physical simulations?
SISSA SIAM Student Chapter
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1:12:01
TAMIDS Digital Twin Lab Seminar: Physics-guided Data-driven Simulations (Dr. Youngsoo Choi)
Texas A&M Institute of Data Science
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1:20:19
55:31
HLCS | Interpretable and Explainable Data-Driven Methods for Physical Simulations
Inside Livermore Lab
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1:06:47
Latent space dynamics identification – Youngsoo Choi
IBS Biomedical Mathematics Group
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1:03:05
DDPS | Bridging numerical methods and deep learning with physics-constrained differentiable solvers
Inside Livermore Lab
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1:06:26
DDPS | Differentiable Physics Simulations for Deep Learning
Inside Livermore Lab
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1:15:15
DDPS | Machine Learning and Physics-based Simulations – Yin and Yang of Industrial Digit
Inside Livermore Lab
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1:02:43
DDPS | Scaling Up AI: Embedding Physics Modeling into End-to-end Learning and Harnessing Projection
Inside Livermore Lab
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20:44
AE for Nonlinear Physics-Constrained Data-Driven Computational Framework: Biological Tissue Modeling
MLPS - Combining AI and ML with Physics Sciences
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1:16:15
DDPS | Input-space Scientific machine learning for PDE-constrained optimization of geometries
Inside Livermore Lab
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13:29
1:02:00
DDPS | The Nexus of Machine Learning, Physics-based Modeling, and Uncertainty Quantification
Inside Livermore Lab
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