Fields- Third Symposium on Machine Learning and Dynamical Systems

  1. Title:
    Machine Learning and Dynamical Systems Meet in Reproducing Kernel Hilbert Spaces

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  2. Title:
    Nonparametric Learning of Interaction Kernels in Interacting Particle Systems

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  3. Title:
    Compositional Features and Neural Network Complexity for Dynamical Systems

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  4. Title:
    From Rough Paths to Streamed Data

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  5. Title:
    Some Time, Some Space, and Some Equations: Machine Learning of Model Error in Dynamical Systems

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  6. Title:
    Learning Dynamical Systems

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  7. Title:
    Multiscale Perturbed Gradient Descent: Chaotic Regularization and Heavy-Tailed Limits

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  8. Title:
    Creation & Annihilation of Spurious Minima in Shallow Neural Networks

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  9. Title:
    A Stochastic Variant of Replicator Dynamics in Zero-Sum Games and Its Invariant Measures

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  10. Title:
    Momentum Stiefel Optimizer, with Applications to Orthogonal Attention, and Optimal Transport

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  11. Title:
    A Proximal Method for Sampling

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  12. Title:
    r-Adaptivity, Deep Learning and the Deep Ritz Method

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  13. Title:
    Approximation Theory of Deep Learning from the Dynamical Viewpoint

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  14. Title:
    Predicting the Impact of Treatment over Time with Uncertainty Aware Neural Differential Equations

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  15. Title:
    Active Learning in Efficient Estimate for Basin Stability of Dynamic Networks

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  16. Title:
    Deep Learning for Nonlinear Stability Analysis in Dynamical Systems

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  17. Title:
    Dissipative Deep Neural Dynamical Systems

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  18. Title:
    Diffrax: Numerical Differential Equation Solvers in JAX

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  19. Title:
    Optimal Transport for Learning Chaotic Dynamics via Invariant Measures

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  20. Title:
    A Coarse-Graining Approach to Mapping Cortical Parameter Space

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