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Viewing Publication 1 - 77 from 77

2023

FAM: Relative Flatness Aware MinimizationLinara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp. tagml 2023: 37-49 [doi]

Global and Relative Topological Features from Homological Invariants of Subsampled DatasetsJens Agerberg, Wojciech Chachólski, Ryan Ramanujam. tagml 2023: 302-312 [doi]

Sumformer: Universal Approximation for Efficient TransformersSilas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok. tagml 2023: 72-86 [doi]

Metric Space Magnitude and Generalisation in Neural NetworksRayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar. tagml 2023: 242-253 [doi]

A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian ManifoldsIlyes Batatia. tagml 2023: 426-436 [doi]

An Exact Kernel Equivalence for Finite Classification ModelsBrian Wesley Bell, Michael Geyer, David Glickenstein, Amanda S. Fernandez, Juston Moore. tagml 2023: 206-217 [doi]

Breaking the Structure of Multilayer Perceptrons with Complex TopologiesTommaso Boccato, Matteo Ferrante, Andrea Duggento, Nicola Toschi. tagml 2023: 289-301 [doi]

Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical ProjectionsClément Bonet, Laetitia Chapel, Lucas Drumetz, Nicolas Courty. tagml 2023: 334-370 [doi]

Topological Feature SelectionAntonio Briola, Tomaso Aste. tagml 2023: 534-556 [doi]

An ML approach to resolution of singularitiesGergely Bérczi, Honglu Fan, Mingcong Zeng. tagml 2023: 469-487 [doi]

Equivariant Self-supervised Deep Pose Estimation for Cryo EMGabriele Cesa, Kumar Pratik, Arash Behboodi. tagml 2023: 21-36 [doi]

The Weisfeiler-Lehman Distance: Reinterpretation and Connection with GNNsSamantha Chen, Sunhyuk Lim, Facundo Mémoli, Zhengchao Wan, Yusu Wang 0001. tagml 2023: 404-425 [doi]

Topologically Attributed Graphs for Shape DiscriminationJustin Curry, Washington Mio, Tom Needham, Osman Berat Okutan, Florian Russold. tagml 2023: 87-101 [doi]

Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023, Honolulu, HI, USATimothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn, editors, Volume 221 of Proceedings of Machine Learning Research, PMLR, 2023. [doi]

PrefaceTimothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn. tagml 2023: 1-2 [doi]

Can strong structural encoding reduce the importance of Message Passing?Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni. tagml 2023: 278-288 [doi]

Learning Lie Group Symmetry Transformations with Neural NetworksAlex Gabel, Victoria Klein, Riccardo Valperga, Jeroen S. W. Lamb, Kevin Webster, Rick Quax, Efstratios Gavves. tagml 2023: 50-59 [doi]

Learning To See Topological Properties In 4D Using Convolutional Neural NetworksKhalil Mathieu Hannouch, Stephan K. Chalup. tagml 2023: 437-454 [doi]

Product Manifold Learning with Independent Coordinate SelectionJesse He, Tristan Brugère, Gal Mishne. tagml 2023: 267-277 [doi]

Explaining Graph Neural Networks Using Interpretable Local SurrogatesFarzaneh Heidari, Perouz Taslakian, Guillaume Rabusseau. tagml 2023: 146-155 [doi]

Episodic Memory Theory of Recurrent Neural Networks: Insights into Long-Term Information Storage and ManipulationArjun Karuvally, Peter DelMastro, Hava T. Siegelmann. tagml 2023: 371-383 [doi]

Bridging Equational Properties and Patterns on Graphs: an AI-Based ApproachOguzhan Keskin, Alisia Maria Lupidi, Stefano Fioravanti, Lucie Charlotte Magister, Pietro Barbiero, Pietro Lio, Francesco Giannini. tagml 2023: 156-168 [doi]

MASIL: Towards Maximum Separable Class Representation for Few Shot Class Incremental LearningAnant Khandelwal. tagml 2023: 519-533 [doi]

One-Shot Neural Network Pruning via Spectral Graph SparsificationSteinar Laenen. tagml 2023: 60-71 [doi]

Deep Networks as Paths on the Manifold of Neural RepresentationsRichard D. Lange, Devin Kwok, Jordan Kyle Matelsky, Xinyue Wang, David Rolnick, Konrad Kording. tagml 2023: 102-133 [doi]

On Explicit Curvature Regularization in Deep Generative ModelsYonghyeon Lee, Frank C. Park 0001. tagml 2023: 505-518 [doi]

Linear Regression on Manifold Structured Data: the Impact of Extrinsic Geometry on SolutionsLiangchen Liu, Juncai He, Yen-Hsi Tsai. tagml 2023: 557-576 [doi]

ReLU Neural Networks, Polyhedral Decompositions, and Persistent HomologyYajing Liu, Christina M. Cole, Chris Peterson 0001, Michael Kirby. tagml 2023: 455-468 [doi]

On genuine invariance learning without weight-tyingArtem Moskalev, Anna Sepliarskaia, Erik J. Bekkers, Arnold W. M. Smeulders. tagml 2023: 218-227 [doi]

Geometrically Regularized Wasserstein Dictionary LearningMarshall Mueller, Shuchin Aeron, James M. Murphy, Abiy Tasissa. tagml 2023: 384-403 [doi]

A margin-based multiclass generalization bound via geometric complexityMichael Munn, Benoit Dherin, Javier Gonzalvo. tagml 2023: 189-205 [doi]

Non-linear Embeddings in Hilbert Simplex GeometryFrank Nielsen, Ke Sun 0001. tagml 2023: 254-266 [doi]

Fisher-Rao and pullback Hilbert cone distances on the multivariate Gaussian manifold with applications to simplification and quantization of mixturesFrank Nielsen. tagml 2023: 488-504 [doi]

ICML 2023 Topological Deep Learning Challenge: Design and ResultsMathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen 0001, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane. tagml 2023: 3-8 [doi]

Unsupervised Embedding Quality EvaluationAnton Tsitsulin, Marina Munkhoeva, Bryan Perozzi. tagml 2023: 169-188 [doi]

Learned Gridification for Efficient Point Cloud ProcessingPutri A. van der Linden, David W. Romero, Erik J. Bekkers. tagml 2023: 9-20 [doi]

Homological Neural Networks: A Sparse Architecture for Multivariate ComplexityYuanrong Wang, Antonio Briola, Tomaso Aste. tagml 2023: 228-241 [doi]

GRIL: A $2$-parameter Persistence Based Vectorization for Machine LearningCheng Xin, Soham Mukherjee, Shreyas N. Samaga, Tamal K. Dey. tagml 2023: 313-333 [doi]

Visualizing and Analyzing the Topology of Neuron Activations in Deep Adversarial TrainingYoujia Zhou, Yi Zhou 0017, Jie Ding 0002, Bei Wang 0001. tagml 2023: 134-145 [doi]

2022

Geodesic Properties of a Generalized Wasserstein Embedding for Time Series AanalysisShiying Li 0002, Abu Hasnat Mohammad Rubaiyat, Gustavo K. Rohde. tagml 2022: 216-225 [doi]

Zeroth-Order Topological Insights into Iterative Magnitude PruningAishwarya H. Balwani, Jakob Krzyston. tagml 2022: 6-16 [doi]

A Topological characterisation of Weisfeiler-Leman equivalence classesJacob Bamberger. tagml 2022: 17-27 [doi]

Sheaf Neural Networks with Connection LaplaciansFederico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò. tagml 2022: 28-36 [doi]

Nearest Class-Center Simplification through Intermediate LayersIdo Ben-Shaul, Shai Dekel. tagml 2022: 37-47 [doi]

Local Distance Preserving Auto-encoders using Continuous kNN GraphsNutan Chen, Patrick van der Smagt, Botond Cseke. tagml 2022: 55-66 [doi]

Diversified Multiscale Graph Learning with Graph Self-CorrectionYuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong. tagml 2022: 48-54 [doi]

The Manifold Scattering Transform for High-Dimensional Point Cloud DataJoyce Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Matthew D. Vesely, Smita Krishnaswamy, Michael Perlmutter. tagml 2022: 67-78 [doi]

Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, VirtualAlexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf, editors, Volume 196 of Proceedings of Machine Learning Research, PMLR, 2022. [doi]

PrefaceAlexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf. tagml 2022: 1-5 [doi]

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many MapsElizabeth Coda, Nico Courts, Colby Wight, Loc Truong, WoongJo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge. tagml 2022: 79-85 [doi]

A Geometrical Approach to Finding Difficult Examples in LanguageDebajyoti Datta, Shashwat Kumar, Laura E. Barnes, P. Thomas Fletcher. tagml 2022: 86-95 [doi]

RipsNet: a general architecture for fast and robust estimation of the persistent homology of point cloudsThibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal. tagml 2022: 96-106 [doi]

A Simple and Universal Rotation Equivariant Point-Cloud NetworkBen Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym. tagml 2022: 107-115 [doi]

The Shape of Words - topological structure in natural language dataStephen Fitz. tagml 2022: 116-123 [doi]

Graph Convolutional Networks from the Perspective of Sheaves and the Neural Tangent KernelThomas Gebhart. tagml 2022: 124-132 [doi]

Two-dimensional visualization of large document libraries using t-SNERita González-Márquez, Philipp Berens, Dmitry Kobak. tagml 2022: 133-141 [doi]

On the Surprising Behaviour of \textttnode2vecCelia Hacker, Bastian Rieck. tagml 2022: 142-151 [doi]

Riemannian CUR Decompositions for Robust Principal Component AnalysisKeaton Hamm, Mohamed Meskini, HanQin Cai. tagml 2022: 152-160 [doi]

Evaluating Disentanglement in Generative Models Without Knowledge of Latent FactorsChester Holtz, Gal Mishne, Alexander Cloninger. tagml 2022: 161-171 [doi]

Multiresolution Matrix Factorization and Wavelet Networks on GraphsTruong-Son Hy, Risi Kondor. tagml 2022: 172-182 [doi]

Random Filters for Enriching the Discriminatory power of Topological RepresentationsGrayson Jorgenson, Henry Kvinge, Tegan Emerson, Colin C. Olson. tagml 2022: 183-188 [doi]

TopTemp: Parsing Precipitate Structure from Temper TopologyLara Kassab, Scott Howland, Henry Kvinge, Keerti Sahithi Kappagantula, Tegan Emerson. tagml 2022: 199-205 [doi]

Rethinking Persistent Homology For Visual RecognitionEkaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh. tagml 2022: 206-215 [doi]

REMuS-GNN: A Rotation-Equivariant Model for Simulating Continuum DynamicsMario Lino, Stathi Fotiadis, Anil A. Bharath, Chris D. Cantwell. tagml 2022: 226-236 [doi]

Persistent tor-algebra based stacking ensemble learning (PTA-SEL) for protein-protein binding affinity predictionXiang Liu, Kelin Xia. tagml 2022: 237-247 [doi]

Deoscillated Adaptive Graph Collaborative FilteringZhiwei Liu, Lin Meng, Fei Jiang, Jiawei Zhang 0001, Philip S. Yu. tagml 2022: 248-257 [doi]

Sparsifying the Update Step in Graph Neural NetworksJohannes F. Lutzeyer, Changmin Wu, Michalis Vazirgiannis. tagml 2022: 258-268 [doi]

Multi-Scale Physical Representations for Approximating PDE Solutions with Graph Neural OperatorsLéon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari. tagml 2022: 332-340 [doi]

Multi-scale Physical Representations for Approximating PDE Solutions with Graph Neural OperatorsLéon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari. tagml 2022: 332-339 [doi]

Robust $L_p$-Norm Linear Discriminant Analysis with Proxy Matrix OptimizationNavya Nagananda, Breton L. Minnehan, Andreas E. Savakis. tagml 2022: 277-286 [doi]

The PWLR graph Representation: A Persistent Weisfeiler-Lehman Scheme with Random Walks for Graph ClassificationSun-Woo Park, Yun Young Choi, Dosang Joe, U Jin Choi, Youngho Woo. tagml 2022: 287-297 [doi]

CubeRep: Learning Relations Between Different Views of DataRishi Sonthalia, Anna C. Gilbert, Matthew Durham. tagml 2022: 298-303 [doi]

Stochastic Parallelizable Eigengap Dilation for Large Graph ClusteringElise van der Pol, Ian Gemp, Yoram Bachrach. tagml 2022: 304-311 [doi]

Score Matching for Truncated Density Estimation on a ManifoldDaniel J. Williams, Song Liu. tagml 2022: 312-321 [doi]

GALE: Globally Assessing Local ExplanationsPeter Xenopoulos, Gromit Chan, Harish Doraiswamy, Luis Gustavo Nonato, Brian Barr, Cláudio T. Silva. tagml 2022: 322-331 [doi]

APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTIONKai Yi, Jialin Chen, Yu Guang Wang 0001, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann. tagml 2022: 189-198 [doi]

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