Topological Data Analysis for Neural Network Analysis: A Comprehensive Survey

no code implementations • 10 Dec 2023 • Rubén Ballester, Carles Casacuberta, Sergio Escalera

We discuss different strategies to obtain topological information from data and neural networks by means of TDA.

Model Selection Topological Data Analysis

ICML 2023 Topological Deep Learning Challenge : Design and Results

1 code implementation • 26 Sep 2023 • Mathilde Papillon, Mustafa Hajij, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Tolga Birdal, Tamal Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Robin Walters, Jens Agerberg, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernardez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Rubén Ballester, Kalyan Nadimpalli, Alexander Nikitin, Abraham Rabinowitz, Alessandro Salatiello, Simone Scardapane, Luca Scofano, Suraj Singh, Jens Sjölund, Pavel Snopov, Indro Spinelli, Lev Telyatnikov, Lucia Testa, Maosheng Yang, Yixiao Yue, Olga Zaghen, Ali Zia, Nina Miolane

This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning.

Decorrelating neurons using persistence

1 code implementation • 9 Aug 2023 • Rubén Ballester, Carles Casacuberta, Sergio Escalera

We propose a novel way to improve the generalisation capacity of deep learning models by reducing high correlations between neurons.

Predicting the generalization gap in neural networks using topological data analysis

1 code implementation • 23 Mar 2022 • Rubén Ballester, Xavier Arnal Clemente, Carles Casacuberta, Meysam Madadi, Ciprian A. Corneanu, Sergio Escalera

Understanding how neural networks generalize on unseen data is crucial for designing more robust and reliable models.

Topological Data Analysis