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Exploring System Dynamics in the Natural World with AI →0/7
1

Model Scale Versus Domain Knowledge in Long-Term Forecasting of Chaos

45:04
2

Operator Learning in Theory and Practice

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3

Science Education for AI: Beyond AI in Science Education

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From Polar Ice to Rising Seas: Advancing Climate Science with Machine Learning

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5

From Scheduled to Predictive Maintenance in Hydropower using AI

58:04
6

Data-Driven Approaches to Mitigate Chalk Influxes

39:43
7

Physical Insights from Discriminative and Generative Models for Frictional Surface Design

40:32

Physical Insights from Discriminative and Generative Models for Frictional Surface Design

Anders Malthe-SørenssenUT Austin

Professor

40:32·2024·graduate level

Anders Malthe-Sørenssen delves into how machine learning models can yield physical insights for designing novel frictional surfaces at a fundamental level.

AI & MLEngineeringStatistical Learning & CausalityControl & Dynamical SystemsComplex Systems & Scalingfrictional surfaces

Anders Malthe-Sørenssen (U Oslo) - Physical insights from discriminative and generative models for frictional surface design

Source: UiO Realfagsbiblioteket via YouTubeWatch on YouTube
LecturerAll lecturers →
Anders Malthe-Sørenssen

Professor

1 course · 7 lecturesCanon
Referenced inHacker News
Previous · Lecture 6

Data-Driven Approaches to Mitigate Chalk Influxes

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