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Volume 221: Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023,
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Editors: Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
Preface
; 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
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:3-8
[abs][Download PDF]
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
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:21-36
FAM: Relative Flatness Aware Minimization
; 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
; 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
; 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
; 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
; 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
; 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
; 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
; 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
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:156-168
Unsupervised Embedding Quality Evaluation
; 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
; 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
; 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
; 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
; 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
; 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
; 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
; 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?
; 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
; 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
; 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
; 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
; 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
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:371-383
Geometrically Regularized Wasserstein Dictionary Learning
; 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
; 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
; 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
; 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
; 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
; 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
; 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
; 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
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:519-533
Topological Feature Selection
; 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
; Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:557-576
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