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Editors: Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
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Preface
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:1-2
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ICML 2023 Topological Deep Learning Challenge: Design and Results
Mathilde Papillon, Mustafa Hajij, Audun Myers, Helen Jenne, Johan Mathe, Theodore Papamarkou, Aldo Guzmán-Sáenz, Neal Livesay, Tamal Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, German Magai, Gleb Bazhenov, Guillermo Bernardez, Indro Spinelli, Jens Agerberg, Kalyan Nadimpalli, Lev Telyatninkov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Hausner, Paul Snopoff, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Karthikeyan Natesan Ramamurthy, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:3-8
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Learned Gridification for Efficient Point Cloud Processing
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:9-20
Equivariant Self-supervised Deep Pose Estimation for Cryo EM
Gabriele Cesa, Kumar Pratik, Arash Behboodi; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:21-36
FAM: Relative Flatness Aware Minimization
Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:37-49
Learning Lie Group Symmetry Transformations with Neural Networks
Alex Gabel, Victoria Klein, Riccardo Valperga, Jeroen S. W. Lamb, Kevin Webster, Rick Quax, Efstratios Gavves; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:50-59
One-Shot Neural Network Pruning via Spectral Graph Sparsification
Steinar Laenen; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:60-71
Sumformer: Universal Approximation for Efficient Transformers
Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:72-86
Topologically Attributed Graphs for Shape Discrimination
Justin Curry, Washington Mio, Tom Needham, Osman Berat Okutan, Florian Russold; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:87-101
Deep Networks as Paths on the Manifold of Neural Representations
Richard D Lange, Devin Kwok, Jordan Kyle Matelsky, Xinyue Wang, David Rolnick, Konrad Kording; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:102-133
Visualizing and Analyzing the Topology of Neuron Activations in Deep Adversarial Training
Youjia Zhou, Yi Zhou, Jie Ding, Bei Wang; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:134-145
Explaining Graph Neural Networks Using Interpretable Local Surrogates
Farzaneh Heidari, Perouz Taslakian, Guillaume Rabusseau; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:146-155
Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach
Oguzhan Keskin, Alisia Maria Lupidi, Stefano Fioravanti, Lucie Charlotte Magister, Pietro Barbiero, Pietro Lio, Francesco Giannini; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:156-168
Unsupervised Embedding Quality Evaluation
Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:169-188
A margin-based multiclass generalization bound via geometric complexity
Michael Munn, Benoit Dherin, Javier Gonzalvo; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:189-205
An Exact Kernel Equivalence for Finite Classification Models
Brian Wesley Bell, Michael Geyer, David Glickenstein, Amanda S Fernandez, Juston Moore; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:206-217
On genuine invariance learning without weight-tying
Artem Moskalev, Anna Sepliarskaia, Erik J Bekkers, Arnold W.M. Smeulders; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:218-227
Homological Neural Networks: A Sparse Architecture for Multivariate Complexity
Yuanrong Wang, Antonio Briola, Tomaso Aste; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:228-241
Metric Space Magnitude and Generalisation in Neural Networks
Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:242-253
Non-linear Embeddings in Hilbert Simplex Geometry
Frank Nielsen, Ke Sun; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:254-266
Product Manifold Learning with Independent Coordinate Selection
Jesse He, Tristan Brugère, Gal Mishne; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:267-277
Can strong structural encoding reduce the importance of Message Passing?
Floor Eijkelboom, Erik J Bekkers, Michael M. Bronstein, Francesco Di Giovanni; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:278-288
Breaking the Structure of Multilayer Perceptrons with Complex Topologies
Tommaso Boccato, Matteo Ferrante, Andrea Duggento, Nicola Toschi; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:289-301
Global and Relative Topological Features from Homological Invariants of Subsampled Datasets
Jens Agerberg, Wojciech Chacholski, Ryan Ramanujam; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:302-312
GRIL: A $2$-parameter Persistence Based Vectorization for Machine Learning
Cheng Xin, Soham Mukherjee, Shreyas N. Samaga, Tamal K. Dey; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:313-333
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections
Clément Bonet, Laetitia Chapel, Lucas Drumetz, Nicolas Courty; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:334-370
Episodic Memory Theory of Recurrent Neural Networks: Insights into Long-Term Information Storage and Manipulation
Arjun Karuvally, Peter DelMastro, Hava T Siegelmann; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:371-383
Geometrically Regularized Wasserstein Dictionary Learning
Marshall Mueller, Shuchin Aeron, James M. Murphy, Abiy Tasissa; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:384-403
The Weisfeiler-Lehman Distance: Reinterpretation and Connection with GNNs
Samantha Chen, Sunhyuk Lim, Facundo Memoli, Zhengchao Wan, Yusu Wang; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:404-425
A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds
Ilyes Batatia; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:426-436
Learning To See Topological Properties In 4D Using Convolutional Neural Networks
Khalil Mathieu Hannouch, Stephan Chalup; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:437-454
ReLU Neural Networks, Polyhedral Decompositions, and Persistent Homology
Yajing Liu, Christina M Cole, Chris Peterson, Michael Kirby; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:455-468
An ML approach to resolution of singularities
Gergely Berczi, Honglu Fan, Mingcong Zeng; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:469-487
Fisher-Rao and pullback Hilbert cone distances on the multivariate Gaussian manifold with applications to simplification and quantization of mixtures
Frank Nielsen; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:488-504
On Explicit Curvature Regularization in Deep Generative Models
Yonghyeon Lee, Frank C. Park; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:505-518
MASIL: Towards Maximum Separable Class Representation for Few Shot Class Incremental Learning
Anant Khandelwal; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:519-533
Topological Feature Selection
Antonio Briola, Tomaso Aste; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:534-556
Linear Regression on Manifold Structured Data: the Impact of Extrinsic Geometry on Solutions
Liangchen Liu, Juncai He, Yen-Hsi Tsai; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:557-576
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