Explore cutting-edge research on Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections in this 24-minute conference talk by Edward De Brouwer from Yale University. Delivered at the Fourth Symposium on Machine Learning and Dynamical Systems, hosted by the Fields Institute on July 11, 2024, this presentation delves into advanced concepts at the intersection of machine learning and dynamical systems. Gain insights into innovative approaches that combine neural differential equations with orthogonal polynomial projections, potentially revolutionizing the field of computational modeling and prediction.
Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
Overview
Syllabus
Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
Taught by
Fields Institute
Related Courses
-
Continuum Attention for Neural Operators
-
Machine Learning Practical Workout | 8 Real-World Projects
-
Data-Driven Modeling of Unknown Systems with Deep Neural Networks
-
Koopman-Based Generalization Bound for Neural Networks
-
Differential Equations and Dynamical Systems - Overview
-
Dissipative Deep Neural Dynamical Systems
