data-driven discovery

Pick anything below and it plays in the bar at the foot of the window — and keeps playing while you go on browsing the directory.

1. 1▶Michael Mahoney - Why Deep Learning WorksPhysics Informed Machine Learning WorkshopNotes
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2. 2▶Benjamin Peherstorfer - Data generation for learning reduced models with operator inferencePhysics Informed Machine Learning WorkshopNotes
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3. 3▶Kevin Carlberg - Breaking Komolgorov-Width Barriers using Deep LearningPhysics Informed Machine Learning WorkshopNotes
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4. 4▶Karthik Duraisamy - Physics constrained probabilistic learning of Koopman decompositionsPhysics Informed Machine Learning WorkshopNotes
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5. 5▶Aleksandr Aravkin - Algorithms for Nonsmooth, Nonconvex Problems in Data-Driven DiscoveryPhysics Informed Machine Learning WorkshopNotes
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6. 6▶Alex Gorodetsky - Scalable Learning of Dynamical SystemsPhysics Informed Machine Learning WorkshopNotes
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7. 7▶Emily Fox - Flexibility, Interpretability, and Scalability in Time Series ModelingPhysics Informed Machine Learning WorkshopNotes
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8. 8▶Michael Brenner - Machine Learning for Partial Differential EquationsPhysics Informed Machine Learning WorkshopNotes
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9. 9▶Charbel Farhat - Probabilistic Physics-Based Machine Learning for Digital TwinsPhysics Informed Machine Learning WorkshopNotes
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10. 10▶Kathleen Champion - Data-driven discovery of coordinates and governing equationsPhysics Informed Machine Learning WorkshopNotes
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11. 11▶Steve Brunton - Discovering interpretable and generalizable dynamical systems from dataPhysics Informed Machine Learning WorkshopNotes
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12. 12▶Benjamin Erichson - Shallow Learning for Flow Reconstruction with Limited Sensors and Limited DataPhysics Informed Machine Learning WorkshopNotes
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13. 13▶Paris Perdikaris - Data-driven modeling of stochastic systems using physics-aware deep learningPhysics Informed Machine Learning WorkshopNotes
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