👉 Complete articles on Geometric Deep Learning, Graph Neural Networks, Topological Data Analysis with exercises are available on my Substack newsletter Hands-on Geometric Deep Learning The authors ...

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library ...

In the rapidly evolving field of artificial intelligence (AI), machine learning (ML) stands as a cornerstone, driving innovation across industries. Among the myriad of tools and frameworks available, ...

Composer is an open-source deep learning training library by MosaicML. Built on top of PyTorch, the Composer library makes it easier to implement distributed training workflows on large-scale clusters ...

A visual web interface hosted on GitHub Pages for building YAML configuration files without editing text by hand. Supports the Training and Predict workflows.

A second obstacle relates to the development of new probabilistic models. From the perspective of developers, there are many necessary routines to implement in support of a probabilistic model, ...

Department of Mathematics and Computer Science, Freie Universität, 14195 Berlin, Germany Department of Physics, Freie Universität, 14195 Berlin, Germany Department of Chemistry, Rice University, ...