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Aleksandr Aravkin - Algorithms for Nonsmooth, Nonconvex Problems in Data-Driven Discovery
DDPS | The Nexus of Machine Learning, Physics-based Modeling, and Uncertainty Quantification
DDPS | Scientific Machine Learning through the Lens of Physics-Informed Neural Networks
DDPS | AI for data-driven simulations in Physics
DDPS | When and why physics-informed neural networks fail to train by Paris Perdikaris
George Karniadakis - From PINNs to DeepOnets
SciFM26 Panel 4 - Physics-Informed AI: When Should Models Learn Physics vs. Be Told It
No equations, no variables: data driven (and physics informed) dynamic models
DDPS | A mathematical understanding of modern Machine Learning: theory, algorithms and applications
Paris Perdikaris - Data-driven modeling of stochastic systems using physics-aware deep learning
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Last Updated: August 21, 2026
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