"geometric deep learning" Papers

17 papers found

AneuG-Flow: A Large-Scale Synthetic Dataset of Diverse Intracranial Aneurysm Geometries and Hemodynamics

Wenhao Ding, Yiying Sheng, Simão de Castro et al.

NEURIPS 2025oral

Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing

Peter Lippmann, Gerrit Gerhartz, Roman Remme et al.

ICLR 2025arXiv:2405.15389
14
citations

Continuous Simplicial Neural Networks

Aref Einizade, Dorina Thanou, Fragkiskos Malliaros et al.

NEURIPS 2025arXiv:2503.12919
2
citations

CosmoBench: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning

Teresa Huang, Richard Stiskalek, Jun-Young Lee et al.

NEURIPS 2025arXiv:2507.03707
2
citations

Curvature-aware Graph Attention for PDEs on Manifolds

Yunfeng Liao, Jiawen Guan, Xiucheng Li

ICML 2025

Discovering Group Structures via Unitary Representation Learning

Dongsung Huh

ICLR 2025
2
citations

On the Expressive Power of Sparse Geometric MPNNs

Yonatan Sverdlov, Nadav Dym

ICLR 2025arXiv:2407.02025
6
citations

An Intrinsic Vector Heat Network

Alexander Gao, Maurice Chu, Mubbasir Kapadia et al.

ICML 2024arXiv:2406.09648
1
citations

CliffPhys: Camera-based Respiratory Measurement using Clifford Neural Networks

Omar Ghezzi, Giuseppe Boccignone, Giuliano Grossi et al.

ECCV 2024
3
citations

Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold

Tingting Dan, Ziquan Wei, Won Hwa Kim et al.

ICML 2024arXiv:2405.16357
6
citations

Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes

Jaehyeong Jo, Sung Ju Hwang

ICML 2024arXiv:2310.07216
16
citations

Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation

6428 Can Xu, Haosen Wang, Weigang Wang et al.

AAAI 2024paperarXiv:2401.02683
18
citations

GeoMFormer: A General Architecture for Geometric Molecular Representation Learning

Tianlang Chen, Shengjie Luo, Di He et al.

ICML 2024arXiv:2406.16853
9
citations

Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics

Siqi Miao, Zhiyuan Lu, Mia Liu et al.

ICML 2024arXiv:2402.12535
13
citations

O$n$ Learning Deep O($n$)-Equivariant Hyperspheres

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck et al.

ICML 2024arXiv:2305.15613
2
citations

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Bruno Gavranović, Paul Lessard, Andrew Dudzik et al.

ICML 2024arXiv:2402.15332
18
citations

Position: Topological Deep Learning is the New Frontier for Relational Learning

Theodore Papamarkou, Tolga Birdal, Michael Bronstein et al.

ICML 2024arXiv:2402.08871
63
citations