Neural ODEs and Neural PDEs
A unified, rigorous formulation of Neural ODEs and Neural PDEs.
Recent content on dani2442's Blog
A unified, rigorous formulation of Neural ODEs and Neural PDEs.
Why the HJB is Bellman's equation in continuous time, why continuous time matters, and how to solve the resulting control problem with neural policy iteration.
Why the HJB is Bellman's equation in continuous time, why continuous time matters, and how to solve the resulting control problem with neural policy iteration.
An overview of the Peter-Weyl theorem and its applications in machine learning.
Supply compounds forever, but demand (attention) doesn't.
Generalization bounds and theory for machine learning models.
The future of healthcare in the age of AI.
Why piracy is likely to move to orbit, and how to defend against it.
When answers get cheap, originality becomes scarce
Notes on Tokamak transport PDEs.
Workshop: 'The Mathematics of Scientific Machine Learning and Digital Twins'
An introduction to Higher-Order Attention, Kernel Methods, and G-Metric Spaces.
We live surrounded by metrics
Math and Code
Analysis and Predictions
Analysis, Predictions and Experiments
Analog computing AI
Introduction to Physics-Informed Neural Networks
Introduction to Functional PCA.
Optimization using Differntiable Programming and Neural ODEs.
Introduction to Traffic Flow Dynamics.
Introduction to Bifurcation Theory from simple eigenvalues.
Hi, this is Daniel López Montero. I will upload notes, projects and some thoughts on topics I am interested in. I am a PhD student of Mathematics researching in Machine Learning, and like to program, read and play football, basketball and padel in my spare time.