Contemporary research in this field is largely concerned with either integrating information about the underlying data topology into existing deep-learning models or obtaining novel ways of training on …

Topological Machine Learning (TML) is an emerging field that leverages techniques from algebraic topology to analyze complex data structures in ways that traditional machine learning methods may …

May 26, 2021 · In this paper, we review the state of the art of a nascent field we refer to as “topological machine learning,” i.e., the successful symbiosis of topology-based methods and machine learning …

Nov 22, 2024 · TDL is rapidly becoming a major paradigm in data science. At its core, the field combines the expressive power of deep neural networks (DNNs) with the mathematical rigor of topology.

Feb 29, 2024 · We examine deep learning methods that make use of topological information to understand the shape of data, as well as the use of deep learning in calculating topological signatures.

Aug 1, 2025 · Recent advances in topological signal processing and learning (TSPL) have harnessed these capabilities, enabling innovative methods for filtering, reconstruction, and representation …

Topological deep learning (TDL) is a rapidly evolving field that uses topological features to understand and design deep learning models. This paper posits that TDL is the new frontier for relational learning.

Aug 4, 2025 · It begins with a clear definition of TDL, an extensive glossary, and a detailed discussion of the advantages of using topological structures for modeling heterogeneous data in machine learning.

Jun 14, 2025 · Explore the latest advancements and future directions in topological machine learning, including new techniques and applications.

If you are reading this, you are probably wondering about what topological machine learning can do for you and your projects. The purpose of this page is to provide a pithy and coarse, but hopefully …