3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

6 July 2018

Papers citing "3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data"

50 / 334 papers shown

Title
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function Jason B. Gibson A. Hire P. M. Dee Oscar Barrera Benjamin Geisler P. Hirschfeld R. G. Hennig 13 4 0 29 Jan 2024
Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D Hao-zhe Huang Owen Howell Dian Wang Xu Zhu Robin G. Walters Robert W. Platt 29 22 0 22 Jan 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo Tianlang Chen Aditi S. Krishnapriyan 25 19 0 18 Jan 2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 41 2 0 17 Jan 2024
Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules Joseph C. Kim David Bloore Karan Kapoor Jun Feng Ming-Hong Hao Mengdi Wang 37 7 0 08 Jan 2024
Diffusion-Driven Generative Framework for Molecular Conformation Prediction Bobin Yang Jie Deng Zhenghan Chen Ruoxue Wu DiffM 29 0 0 22 Dec 2023
SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI Benjamin Billot Neel Dey Daniel Moyer M. Hoffmann Esra Abaci Turk B. Gagoski Ellen Grant Polina Golland 3DPC 23 6 0 21 Dec 2023
Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries Alonso Urbano David W. Romero 24 1 0 19 Dec 2023
Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials Teddy Koker Keegan Quigley Eric Taw Kevin Tibbetts Lin Li 20 12 0 08 Dec 2023
Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim Joshua Robinson Stefanie Jegelka Haggai Maron 71 16 0 04 Dec 2023
ShapeMatcher: Self-Supervised Joint Shape Canonicalization, Segmentation, Retrieval and Deformation Yan Di Chenyangguang Zhang Chaowei Wang Ruida Zhang Guangyao Zhai Yanyan Li Bowen Fu Xiangyang Ji Shan Gao 3DPC 21 5 0 18 Nov 2023
Affine Invariance in Continuous-Domain Convolutional Neural Networks A. Mohaddes Johannes Lederer 18 1 0 13 Nov 2023
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer Namkyeong Lee Heewoong Noh Sungwon Kim Dongmin Hyun Gyoung S. Na Chanyoung Park 21 5 0 24 Oct 2023
Symmetry-preserving graph attention network to solve routing problems at multiple resolutions Cong Dao Tran Thong Bach Truong Son-Hy 31 0 0 24 Oct 2023
Learning Layer-wise Equivariances Automatically using Gradients Tycho F. A. van der Ouderaa Alexander Immer Mark van der Wilk MLT 47 12 0 09 Oct 2023
On Accelerating Diffusion-based Molecular Conformation Generation in SE(3)-invariant Space Zihan Zhou Ruiying Liu Tianshu Yu DiffM 30 0 0 07 Oct 2023
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 40 1 0 06 Oct 2023
Ophiuchus: Scalable Modeling of Protein Structures through Hierarchical Coarse-graining SO(3)-Equivariant Autoencoders Allan dos Santos Costa Ilan Mitnikov Mario Geiger Manvitha Ponnapati Tess E. Smidt Joseph Jacobson DiffM 18 3 0 04 Oct 2023
AtomSurf : Surface Representation for Learning on Protein Structures Vincent Mallet Souhaib Attaiki M. Ovsjanikov 36 3 0 28 Sep 2023
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite Stefania Costantini Gianluca Galletti Fabian Fritz Stefan Adami Nikolaus A. Adams 40 13 0 28 Sep 2023
HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery Alvaro Prat Hisham Abdel-Aty Gintautas Kamuntavicius Tanya Paquet P. Norvaisas Piero Gasparotto Roy Tal 23 2 0 22 Sep 2023
E(2)-Equivariant Graph Planning for Navigation Linfeng Zhao Hongyu Li T. Padır Huaizu Jiang Lawson L. S. Wong 25 6 0 22 Sep 2023
Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly Ruihai Wu Chenrui Tie Yushi Du Yan Zhao Hao Dong 28 19 0 13 Sep 2023
Molecular Conformation Generation via Shifting Scores Zihan Zhou Ruiying Liu Chaolong Ying Ruimao Zhang Tianshu Yu DiffM 29 2 0 12 Sep 2023
Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein Simulators Jingbang Chen Yian Wang Xingwei Qu Shuangjia Zheng Yao-Chun Yang Hao Dong Jie Fu 15 0 0 29 Aug 2023
Leveraging Symmetries in Pick and Place Hao-zhe Huang Dian Wang Arsh Tangri Robin G. Walters Robert W. Platt 27 14 0 15 Aug 2023
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds O. Melia Eric Jonas Rebecca Willett OOD 3DPC 18 3 0 27 Jul 2023
Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning? Linfeng Zhao Owen Howell Jung Yeon Park Xu Zhu Robin G. Walters Lawson L. S. Wong 36 1 0 17 Jul 2023
Geometric Neural Diffusion Processes Emile Mathieu Vincent Dutordoir M. Hutchinson Valentin De Bortoli Yee Whye Teh Richard E. Turner DiffM 36 8 0 11 Jul 2023
Equivariant Single View Pose Prediction Via Induced and Restricted Representations Owen Howell David M. Klee Ondrej Biza Linfeng Zhao Robin G. Walters 28 4 0 07 Jul 2023
Learning Lie Group Symmetry Transformations with Neural Networks Alex Gabel Victoria G Klein Riccardo Valperga J. Lamb K. Webster Rick Quax E. Gavves 20 5 0 04 Jul 2023
Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis T. Kuipers Erik J. Bekkers 11 5 0 24 Jun 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 24 131 0 21 Jun 2023
3D molecule generation by denoising voxel grids Pedro H. O. Pinheiro Joshua Rackers J. Kleinhenz Michael R. Maser Omar Mahmood Andrew Watkins Stephen Ra Vishnu Sresht Saeed Saremi DiffM 34 20 0 13 Jun 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni de Fabritiis 24 45 0 10 Jun 2023
Any-dimensional equivariant neural networks Eitan Levin Mateo Díaz 21 6 0 10 Jun 2023
Group Equivariant Fourier Neural Operators for Partial Differential Equations Jacob Helwig Xuan Zhang Cong Fu Jerry Kurtin Stephan Wojtowytsch Shuiwang Ji AI4CE 47 28 0 09 Jun 2023
Scaling Spherical CNNs Carlos Esteves Jean-Jacques E. Slotine A. Makadia GNN LRM 19 13 0 08 Jun 2023
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation Marten Lienen David Ludke Jan Hansen-Palmus Stephan Günnemann DiffM AI4CE 24 23 0 29 May 2023
Investigating how ReLU-networks encode symmetries Georg Bökman Fredrik Kahl 24 6 0 26 May 2023
Learning Lagrangian Fluid Mechanics with E( $3$ )-Equivariant Graph Neural Networks Artur P. Toshev Gianluca Galletti Johannes Brandstetter Stefan Adami Nikolaus A. Adams AI4CE 27 5 0 24 May 2023
Subspace-Configurable Networks Dong Wang O. Saukh Xiaoxi He Lothar Thiele OOD 30 0 0 22 May 2023
Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinement Zhangyang Gao Cheng Tan Stan Z. Li 23 15 0 20 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 26 34 0 18 May 2023
Policy Gradient Methods in the Presence of Symmetries and State Abstractions Prakash Panangaden S. Rezaei-Shoshtari Rosie Zhao D. Meger Doina Precup 25 2 0 09 May 2023
KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory Roman Remme Tobias Kaczun Maximilian Scheurer A. Dreuw Fred Hamprecht 30 9 0 08 May 2023
Geometric Latent Diffusion Models for 3D Molecule Generation Minkai Xu Alexander Powers R. Dror Stefano Ermon J. Leskovec DiffM AI4CE 55 134 0 02 May 2023
DeepReShape: Redesigning Neural Networks for Efficient Private Inference N. Jha Brandon Reagen 28 10 0 20 Apr 2023
$$E(3) \times SO(3)$-Equivariant Networks for Spherical Deconvolution in Diffusion MRI$ $E(3) \times SO(3)$ -Equivariant Networks for Spherical Deconvolution in Diffusion MRI Axel Elaldi Guido Gerig Neel Dey MedIm 14 3 0 12 Apr 2023
Scale-Equivariant Deep Learning for 3D Data Thomas Wimmer Vladimir Golkov H. Dang Moritz Zaiss Andreas K. Maier Daniel Cremers 3DPC MedIm 20 5 0 12 Apr 2023