Start with tutorials to get familiar with the code
Tutorial 1: Train a neural ODE based network on point cloud data set and generating a gif of the resulting time evolution of the neural ODE
Code: 
Code is based on GitHub: borjanG : 2021-dynamical-systems that uses the torchdiffeq package GitHub : rtqichen: torchdiffeq
Code:
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach Motivation This post shows the source code from the paper […]
Clustering in pure-attention hardmax transformers and its role in sentiment analysis This post provides an overview of the results in the paper […]
Author: Daniel Veldman, FAU DCN-AvH Code: || Also available @Daniël’s GitHub In a previous post “Randomized time-splitting in linear-quadratic optimal control“, it […]
The code implements the gradient regularization method of robust training in the setting of neural ODEs. Various jupyter notebooks are included that […]
