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
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods Artur P. Toshev Ludger Paehler A. Panizza Nikolaus A. Adams AI4CE PINN 11 5 0 31 Mar 2023
The G-invariant graph Laplacian E. Rosen Paulina Hoyos Xiuyuan Cheng Joe Kileel Y. Shkolnisky 11 1 0 29 Mar 2023
4D Panoptic Segmentation as Invariant and Equivariant Field Prediction Minghan Zhu Shizong Han H. Cai Shubhankar Borse M. G. Jadidi Fatih Porikli 3DPC 52 15 0 28 Mar 2023
Rethinking SO(3)-equivariance with Bilinear Tensor Networks C. Shimmin Zhelun Li Ema Smith 3DPC 20 0 0 20 Mar 2023
Computing equivariant matrices on homogeneous spaces for Geometric Deep Learning and Automorphic Lie Algebras V. Knibbeler 30 1 0 13 Mar 2023
Predicting Density of States via Multi-modal Transformer Namkyeong Lee Heewoong Noh Sungwon Kim Dongmin Hyun Gyoung S. Na Chanyoung Park 16 3 0 13 Mar 2023
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries Charlotte Loh Seung-Jun Han Shivchander Sudalairaj Rumen Dangovski Kai Xu F. Wenzel Marin Soljacic Akash Srivastava UQCV 39 1 0 04 Mar 2023
Deep Neural Networks with Efficient Guaranteed Invariances M. Rath A. P. Condurache 16 4 0 02 Mar 2023
Leveraging SO(3)-steerable convolutions for pose-robust semantic segmentation in 3D medical data I. Díaz Mario Geiger Richard McKinley 3DPC 11 0 0 01 Mar 2023
Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance Xueyi Liu Ji Zhang Ruizhen Hu Haibin Huang He-Nan Wang Li Yi 3DPC 21 21 0 28 Feb 2023
General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment Liang Xie Yibo Yang Wenxiao Wang Binbin Lin Deng Cai Xiaofei He Ronghua Liang 3DPC 16 2 0 20 Feb 2023
Geometric Clifford Algebra Networks David Ruhe Jayesh K. Gupta Steven De Keninck Max Welling Johannes Brandstetter AI4CE 18 33 0 13 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 28 79 0 07 Feb 2023
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction Zuobai Zhang Minghao Xu A. Lozano Vijil Chenthamarakshan Payel Das Jian Tang DiffM 19 19 0 28 Jan 2023
Modelling Long Range Dependencies in $N$ D: From Task-Specific to a General Purpose CNN David M. Knigge David W. Romero Albert Gu E. Gavves Erik J. Bekkers Jakub M. Tomczak Mark Hoogendoorn J. Sonke 3DV 27 21 0 25 Jan 2023
On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi Cristian Bodnar Simon V. Mathis Taco Cohen Pietro Liò 50 83 0 23 Jan 2023
SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping Bipasha Sen Aditya Agarwal Gaurav Singh B. Brojeshwar Srinath Sridhar Madhava Krishna 3DPC 32 10 0 17 Jan 2023
Equivariant and Steerable Neural Networks: A review with special emphasis on the symmetric group Patrick Krüger Hanno Gottschalk 19 1 0 08 Jan 2023
Equivariant Light Field Convolution and Transformer Yinshuang Xu Jiahui Lei Kostas Daniilidis ViT 19 0 0 30 Dec 2022
Brauer's Group Equivariant Neural Networks Edward Pearce-Crump AI4CE 13 15 0 16 Dec 2022
Implicit Convolutional Kernels for Steerable CNNs Maksim Zhdanov Nico Hoffmann Gabriele Cesa 29 5 0 12 Dec 2022
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 23 59 0 11 Dec 2022
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields Rohith Agaram Shaurya Dewan Rahul Sajnani A. Poulenard Madhava Krishna Srinath Sridhar 33 6 0 05 Dec 2022
Score-based denoising for atomic structure identification Tim Hsu Babak Sadigh N. Bertin Cheol Woo Park James Chapman Vasily V. Bulatov Fei Zhou DiffM 40 6 0 05 Dec 2022
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution A. Poulenard M. Ovsjanikov Leonidas J. Guibas 3DPC 30 2 0 29 Nov 2022
TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis Pavlo Melnyk Andreas Robinson M. Felsberg Maarten Wadenback 3DPC 18 2 0 26 Nov 2022
Transformation-Equivariant 3D Object Detection for Autonomous Driving Hai Wu Chenglu Wen Wei Li Xin Li Ruigang Yang Cheng-i Wang 3DPC 20 87 0 22 Nov 2022
Homomorphic Self-Supervised Learning Thomas Anderson Keller Xavier Suau Luca Zappella SSL 19 2 0 15 Nov 2022
SPE-Net: Boosting Point Cloud Analysis via Rotation Robustness Enhancement Zhaofan Qiu Yehao Li Yu Wang Yingwei Pan Ting Yao Tao Mei 3DPC 19 5 0 15 Nov 2022
Equivariant Networks for Crystal Structures Sekouba Kaba Siamak Ravanbakhsh AI4CE 42 23 0 15 Nov 2022
Rotation-equivariant Graph Neural Networks for Learning Glassy Liquids Representations F. Pezzicoli Guillaume Charpiat François P. Landes 21 6 0 06 Nov 2022
Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation Di Luo Shunyue Yuan J. Stokes B. Clark 21 14 0 06 Nov 2022
Learning the shape of protein micro-environments with a holographic convolutional neural network Michael N. Pun Andrew Ivanov Quinn Bellamy Zachary Montague Colin H. LaMont P. Bradley J. Otwinowski Armita Nourmohammad 11 12 0 05 Nov 2022
Breaking the Symmetry: Resolving Symmetry Ambiguities in Equivariant Neural Networks S. Balachandar A. Poulenard Congyue Deng Leonidas J. Guibas 22 1 0 29 Oct 2022
Transferable E(3) equivariant parameterization for Hamiltonian of molecules and solids Yang Zhong Hongyu Yu Mao Su X. Gong H. Xiang 28 36 0 28 Oct 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks Arash Behboodi Gabriele Cesa Taco S. Cohen 48 17 0 24 Oct 2022
Equivariant Networks for Zero-Shot Coordination Darius Muglich Christian Schroeder de Witt Elise van der Pol Shimon Whiteson Jakob N. Foerster 47 13 0 21 Oct 2022
Structure-based drug design with geometric deep learning Clemens Isert Kenneth Atz G. Schneider 44 104 0 19 Oct 2022
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks Renan A. Rojas-Gomez Teck-Yian Lim A. Schwing Minh Do Raymond A. Yeh 31 9 0 14 Oct 2022
Scale Equivariant U-Net Mateus Sangalli S. Blusseau Santiago Velasco-Forero Jesús Angulo SSeg 25 12 0 10 Oct 2022
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? Henry Kvinge Tegan H. Emerson Grayson Jorgenson Scott Vasquez T. Doster Jesse D. Lew 43 8 0 07 Oct 2022
Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space Gian Marco Visani Michael N. Pun Arman Angaji Armita Nourmohammad BDL 24 3 0 30 Sep 2022
In Search of Projectively Equivariant Networks Georg Bökman Axel Flinth Fredrik Kahl 37 0 0 29 Sep 2022
A Simple Strategy to Provable Invariance via Orbit Mapping Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller AAML 3DPC 18 3 0 24 Sep 2022
PiFold: Toward effective and efficient protein inverse folding Zhangyang Gao Cheng Tan Pablo Chacón Stan Z. Li AI4CE 67 104 0 22 Sep 2022
SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation Z. Su Max Welling M. Pietikäinen Li Liu 3DPC 32 11 0 13 Sep 2022
SELTO: Sample-Efficient Learned Topology Optimization Sören Dittmer David Erzmann Henrik Harms Peter Maass 29 2 0 12 Sep 2022
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 60 80 0 08 Sep 2022
A Feedforward Unitary Equivariant Neural Network P. Ma Terence Chan 23 4 0 25 Aug 2022
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems Qianxiao Li T. Lin Zuowei Shen 21 6 0 18 Aug 2022