ICML 2023 Workshop TAGML Submissions

Edge Importance Scores for Editing Graph Topology to Preserve Fairness
Sree Harsha Tanneru
- Published: 18 Jun 2023, Last Modified: 04 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Infusing invariances in neural representations
Irene Cannistraci, Marco Fumero, Luca Moschella, Valentino Maiorca, Emanuele Rodolà
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Expressive Sign Equivariant Networks for Spectral Geometric Learning
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Desiderata for Representation Learning from Identifiability, Disentanglement, and Group-Structuredness
Hamza Keurti, Patrik Reizinger, Bernhard Schölkopf, Wieland Brendel
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks
David W. Zhang, Miltiadis Kofinas, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Cees G. M. Snoek
- Published: 18 Jun 2023, Last Modified: 28 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Mixed-Curvature Transformers for Graph Representation Learning
Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee
- Published: 18 Jun 2023, Last Modified: 01 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Hyperbolic VAE via Latent Gaussian Distributions
Seunghyuk Cho, Juyong Lee, Dongwoo Kim
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Sample Complexity Bounds for Estimating the Wasserstein Distance under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
- Published: 18 Jun 2023, Last Modified: 03 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Positional Encodings as Group Representations: A Unified Framework
Derek Lim, Hannah Lawrence, Ningyuan Teresa Huang, Erik Henning Thiede
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Which Features are Learned by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman
- Published: 18 Jun 2023, Last Modified: 02 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Fast computation of permutation equivariant layers with the partition algebra
Charles Godfrey, Michael G. Rawson, Davis Brown, Henry Kvinge
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Unsupervised Learning of 3-colorings using Simplicial Higher-Order Neural Networks
Lucas Laird, Robin Walters, Wolfgang Gatterbauer
- Published: 18 Jun 2023, Last Modified: 18 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Evolving Computation Graphs
Andreea Deac, Jian Tang
- Published: 18 Jun 2023, Last Modified: 02 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Equivariant Representation Learning with Equivariant Convolutional Kernel Networks
Soutrik Roy Chowdhury, Johan Suykens
- Published: 18 Jun 2023, Last Modified: 30 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
- Published: 18 Jun 2023, Last Modified: 29 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
On the Relationship Between Data Manifolds and Adversarial Examples
Michael Geyer, Brian Wesley Bell, Amanda S Fernandez, Juston Moore
- Published: 18 Jun 2023, Last Modified: 04 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
UGSL: A Unified Framework for Benchmarking Graph Structure Learning
Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Asynchronous Algorithmic Alignment with Cocycles
Andrew Joseph Dudzik, Tamara von Glehn, Razvan Pascanu, Petar Veličković
- Published: 18 Jun 2023, Last Modified: 02 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Caveats of neural persistence in deep neural networks
Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke
- Published: 18 Jun 2023, Last Modified: 04 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
DeepEMD: A Transformer-based Fast Estimation of the Earth Mover's Distance
Atul Kumar Sinha, François Fleuret
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Group Invariant Global Pooling
Kamil Bujel, Yonatan Gideoni, Chaitanya K. Joshi, Pietro Lio
- Published: 18 Jun 2023, Last Modified: 28 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Polyhedral Complex Extraction from ReLU Networks using Edge Subdivision
Arturs Berzins
- Published: 18 Jun 2023, Last Modified: 27 Jun 2023
- TAGML2023 Poster
- Readers: Everyone
Regression on Latent Spaces for the Analysis of Multi-Condition Single-Cell RNA-Seq Data
Constantin Ahlmann-Eltze, Wolfgang Huber
- Published: 18 Jun 2023, Last Modified: 01 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
The Exact Sample Complexity Gain from Invariances for Kernel Regression
Behrooz Tahmasebi, Stefanie Jegelka
- Published: 18 Jun 2023, Last Modified: 03 Jul 2023
- TAGML2023 Poster
- Readers: Everyone
Learning Polynomial Problems with SL(2)-Equivariance
Hannah Lawrence, Mitchell Tong Harris
- Published: 18 Jun 2023, Last Modified: 02 Jul 2023
- TAGML2023 Poster
- Readers: Everyone