# Accepted Papers

This is the list of all accepted papers. You can find more information
about each submission by following either the *Forum* link or by visiting
our OpenReview Workshop Website. Please note that not all submissions are revised yet.

Congratulations to all authors!

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**A Piece-wise Polynomial Filtering Approach for Graph Neural Networks** (Spotlight presentation)

Vijay Lingam • Chanakya Ajit Ekbote • Manan Sharma • Rahul Ragesh • Arun Iyer • SUNDARARAJAN SELLAMANICKAM

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**An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations**

Florent Bonnet • Jocelyn Ahmed Mazari • Thibaut Munzer • Pierre Yser • patrick gallinari

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**CubeRep: Learning Relations Between Different Views of Data**

Rishi Sonthalia • Anna Gilbert • Matthew Durham

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**Cycle Representation Learning for Inductive Relation Prediction**

Zuoyu Yan • Tengfei Ma • Liangcai Gao • Zhi Tang • Chao Chen

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**Decoupled Graph Neural Networks based on Label Agreement Message Propagation**

Zhicheng An • Zhengwei Wu • Binbin Hu • Zhiqiang Zhang • JUN ZHOU • Yue Wang • Shao-Lun Huang

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**Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment**

Adam Leach • Sebastian M Schmon • Matteo T. Degiacomi • Chris G. Willcocks

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**Diffusion-Based Methods for Estimating Curvature in Data**

Dhananjay Bhaskar • Kincaid MacDonald • Dawson Thomas • Sarah Zhao • Kisung You • Jennifer Paige • Yariv Aizenbud • Bastian Rieck • Ian M Adelstein • Smita Krishnaswamy

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**Diversified Multiscale Graph Learning with Graph Self-Correction**

Yuzhao Chen • Yatao Bian • Jiying Zhang • Xi Xiao • Tingyang Xu • Yu Rong

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**Efficient Representation Learning of Subgraphs by Subgraph-To-Node Translation**

Dongkwan Kim • Alice Oh

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**EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction**

Hannes Stärk • Octavian-Eugen Ganea • Lagnajit Pattanaik • Regina Barzilay • Tommi S. Jaakkola

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**Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps**

Elizabeth Coda • Nico Courts • Colby Wight • Loc Truong • WoongJo Choi • Charles Godfrey • Tegan Emerson • Keerti Kappagantula • Henry Kvinge

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**Gauge Equivariant Deep Q-Learning on Discrete Manifolds**

Sourya Basu • Pulkit Katdare • Katherine Rose Driggs-Campbell • Lav R. Varshney

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**Graph Anisotropic Diffusion**

Ahmed A. A. Elhag • Gabriele Corso • Hannes Stärk • Michael M. Bronstein

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**Graph Neural Networks are Dynamic Programmers**

Andrew Dudzik • Petar Veličković

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**Group Symmetry in PAC Learning** (Spotlight presentation)

Bryn Elesedy

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**Heterogeneous manifolds for curvature-aware graph embedding**

Francesco Di Giovanni • Giulia Luise • Michael M. Bronstein

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**HIGH SKIP NETWORKS: A HIGHER ORDER GENERALIZATION OF SKIP CONNECTIONS**

Mustafa Hajij • Karthikeyan Natesan Ramamurthy • Aldo Guzmán-Sáenz • Ghada Za

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**Learning Weighted Product Spaces Representations for Graphs of Heterogeneous Structures**

Tuc Van Nguyen • Dung D. Le • Anh Ta

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**Manifold-aligned Neighbor Embedding**

Mohammad Tariqul Islam • Jason W. Fleischer

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**Message passing all the way up** (Spotlight presentation)

Petar Veličković

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**Message Passing Neural Processes**

Cătălina Cangea • Ben Day • Arian Rokkum Jamasb • Pietro Lio

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**Multi-scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators**

Léon Migus • Yuan Yin • Jocelyn Ahmed Mazari • patrick gallinari

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**Neural Approximation of Extended Persistent Homology on Graphs** (Spotlight presentation)

Zuoyu Yan • Tengfei Ma • Liangcai Gao • Zhi Tang • Yusu Wang • Chao Chen

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**Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs** (Spotlight presentation)

Cristian Bodnar • Francesco Di Giovanni • Benjamin Paul Chamberlain • Pietro Lio • Michael M. Bronstein

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**ON RECOVERABILITY OF GRAPH NEURAL NETWORK REPRESENTATIONS**

Maxim Fishman • Chaim Baskin • Evgenii Zheltonozhskii • Ron Banner • Avi Mendelson

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**On subsampling and inference for multiparameter persistence homology**

Vinoth Nandakumar

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**On the Inadequacy of CKA as a Measure of Similarity in Deep Learning**

MohammadReza Davari • Stefan Horoi • Amine Natik • Guillaume Lajoie • Guy Wolf • Eugene Belilovsky

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**Persistent Tor-algebra based stacking ensemble learning (PTA-SEL) for protein-protein binding affinity prediction**

Xiang LIU • KELIN XIA

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**Pre-training Molecular Graph Representation with 3D Geometry** (Spotlight presentation)

Shengchao Liu • Hanchen Wang • Weiyang Liu • Joan Lasenby • Hongyu Guo • Jian Tang

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**Random Filters for Enriching the Discriminatory Power of Topological Representations**

Tegan Emerson • Grayson Jorgenson • Henry Kvinge • Colin Olson

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**Reducing Learning on Cell Complexes to Graphs**

Fabian Jogl • Maximilian Thiessen • Thomas Gärtner

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**REMuS-GNN: A Rotation-Equivariant Model for Simulating Continuum Dynamics**

Mario Lino Valencia • Stathi Fotiadis • Anil Anthony Bharath • Chris D Cantwell

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**Riemannian Neural SDE: Learning Stochastic Representations on Manifolds**

Sung Woo Park • Hyomin Kim • Hyeseong Kim • Junseok Kwon

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**RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds** (Spotlight presentation)

Thibault de Surrel • Felix Hensel • Mathieu Carrière • Théo Lacombe • Yuichi Ike • Hiroaki Kurihara • Marc Glisse • Frederic Chazal

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**Sign and Basis Invariant Networks for Spectral Graph Representation Learning**

Derek Lim • Joshua David Robinson • Lingxiao Zhao • Tess Smidt • Suvrit Sra • Haggai Maron • Stefanie Jegelka

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**Simplicial Attention Networks**

Christopher Wei Jin Goh • Cristian Bodnar • Pietro Lio

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**Sparsifying the Update Step in Graph Neural Networks**

Johannes F. Lutzeyer • changmin wu • Michalis Vazirgiannis

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**SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks**

Christopher Morris • Gaurav Rattan • Sandra Kiefer • Siamak Ravanbakhsh

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**TopTemp: Parsing Precipitate Structure from Temper Topology** (Spotlight presentation)

Tegan Emerson • Lara Kassab • Scott Howland • Henry Kvinge • Keerti Sahithi Kappagantula

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**Two-dimensional visualization of large document libraries using t-SNE**

Rita González-Márquez • Philipp Berens • Dmitry Kobak

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**WEISFEILER AND LEMAN GO INFINITE: SPECTRAL AND COMBINATORIAL PRE-COLORINGS**

Or Feldman • Amit Boyarski • Shai Feldman • Dani Kogan • Avi Mendelson • Chaim Baskin