Topological Data Analysis (TDA) is a rapidly growing field with tremendous potential for improving machine learning pipelines, unboxing the most intricate deep networks, and creating new geometric features from data.
Since the knowledge barrier that protects TDA might scare some data scientists, the purpose of this track is not only to showcase TDA as a complementary tool to machine learning, but also to lower this barrier and make TDA more intuitive and accessible.
The speakers of this track are all renowned leaders in the topics they present; dynamical system analysis using TDA, analysis of deep networks with TDA, feature engineering via TDA, data visualisation and dimensionality reduction are the main topics discussed in this track.
With Shusen Liu
With Elizabeth Munch
Robert West, Roy Gava, Victor Kristof, Steven Eichenberger, Alexandra Siegel, Lucas Leemann, Rayid Ghani, Sophie Achermann, Alexander Immer, Jacques Savoy, Oana Goga, Christine Choirat, Arianna Ornaghi, Irio Musskopf
10:00-18:00 January 25OnlineMarcel Salathé, Fabio Mainardi, Tome Eftimov, Sharada Mohanty, Philippe Glénat, Timon Zimmermann, Mireille Moser, Ugo Gentile, Christoph Trattner, Enrico Zio, Yamine Bouzembrak, Christian Nils Schwab, Carrol Plummer, Patrizia Catellani, Matthias Graeber, Lorijn van Rooijen, Kristina Gligorić, Lydia Afman, Nourchene Ben Romdhane, Talia Salzmann, Thomas Chen, Gjorgjina Cenikj, Gorjan Popovski, Sola Shirai
09:00-17:00 March 01OnlineMarcel Salathé, Bastian Rieck, Matteo Togninalli, Damian Roqueiro, Christian Bock, Daniel Rueckert, Michael Menden, Stephanie Hyland, Steve Jiang, Danielle Belgrave, Julia Vogt, Tobias Gass, Alistair Johnson, Assaf Gottlieb, Finale Doshi-Velez, Bernice Elger, Vanessa Schumacher
09:10-18:00 March 18Online
AMLD Global