ICML 2023 Workshop TAGML Submissions

On genuine invariance learning without weight-tying
Artem Moskalev, Anna Sepliarskaia, Erik J Bekkers, Arnold W.M. Smeulders
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Learning to Explain Hypergraph Neural Networks
Sepideh Maleki, Ehsan Hajiramezanali, Gabriele Scalia, Tommaso Biancalani, Kangway V. Chuang
- Published: 18 Jun 2023, Last Modified: 25 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Breaking the Curse of Depth in Graph Convolutional Networks via Refined Initialization Strategy
Senmiao Wang, Yupeng Chen, Yushun Zhang, Tian Ding, Ruoyu Sun
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Oral
- Readers: Everyone
Homological Neural Networks: A Sparse Architecture for Multivariate Complexity
Yuanrong Wang, Antonio Briola, Tomaso Aste
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Metric Space Magnitude and Generalisation in Neural Networks
Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Non-linear Embeddings in Hilbert Simplex Geometry
Frank Nielsen, Ke Sun
- Published: 18 Jun 2023, Last Modified: 04 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Product Manifold Learning with Independent Coordinate Selection
Jesse He, Tristan Brugère, Gal Mishne
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Can strong structural encoding reduce the importance of Message Passing?
Floor Eijkelboom, Erik J Bekkers, Michael M. Bronstein, Francesco Di Giovanni
- Published: 18 Jun 2023, Last Modified: 02 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Breaking the Structure of Multilayer Perceptrons with Complex Topologies
Tommaso Boccato, Matteo Ferrante, Andrea Duggento, Nicola Toschi
- Published: 18 Jun 2023, Last Modified: 04 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Global and Relative Topological Features from Homological Invariants of Subsampled Datasets
Jens Agerberg, Wojciech Chacholski, Ryan Ramanujam
- Published: 18 Jun 2023, Last Modified: 29 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
k-Means Clustering with Distance-Based Privacy
Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
- Published: 18 Jun 2023, Last Modified: 28 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Differentially Private Clustering in Data Streams
Alessandro Epasto, Tamalika Mukherjee, Peilin Zhong
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
GRIL: A $2$-parameter Persistence Based Vectorization for Machine Learning
Cheng Xin, Soham Mukherjee, Shreyas N. Samaga, Tamal K. Dey
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Oral
- Readers: Everyone
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections
Clément Bonet, Laetitia Chapel, Lucas Drumetz, Nicolas Courty
- Published: 18 Jun 2023, Last Modified: 26 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Episodic Memory Theory of Recurrent Neural Networks: Insights into Long-Term Information Storage and Manipulation
Arjun Karuvally, Peter DelMastro, Hava T Siegelmann
- Published: 18 Jun 2023, Last Modified: 29 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Geometrically Regularized Wasserstein Dictionary Learning
Marshall Mueller, Shuchin Aeron, James M. Murphy, Abiy Tasissa
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin, Tom Verbin, Nadav Cohen
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
The Weisfeiler-Lehman Distance: Reinterpretation and Connection with GNNs
Samantha Chen, Sunhyuk Lim, Facundo Memoli, Zhengchao Wan, Yusu Wang
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds
Ilyes Batatia
- Published: 18 Jun 2023, Last Modified: 04 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Learning To See Topological Properties In 4D Using Convolutional Neural Networks
Khalil Mathieu Hannouch, Stephan Chalup
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
ReLU Neural Networks, Polyhedral Decompositions, and Persistent Homology
Yajing Liu, Christina M Cole, Chris Peterson, Michael Kirby
- Published: 18 Jun 2023, Last Modified: 21 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Learning Large Graph Property Prediction via Graph Segment Training
Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi
- Published: 18 Jun 2023, Last Modified: 25 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
An ML approach to resolution of singularities
Gergely Berczi, Honglu Fan, Mingcong Zeng
- Published: 18 Jun 2023, Last Modified: 17 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Fisher-Rao and pullback Hilbert cone distances on the multivariate Gaussian manifold with applications to simplification and quantization of mixtures
Frank Nielsen
- Published: 18 Jun 2023, Last Modified: 23 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
On Explicit Curvature Regularization in Deep Generative Models
Yonghyeon Lee, Frank C. Park
- Published: 18 Jun 2023, Last Modified: 07 Jul 2023
- TAGML2023 Poster
- Readers: Everyone