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
Deformation Robust Roto-Scale-Translation Equivariant CNNs Liyao (Mars) Gao Guang Lin Wei-wei Zhu 20 8 0 22 Nov 2021
Enabling equivariance for arbitrary Lie groups L. MacDonald Sameera Ramasinghe Simon Lucey AAML 19 25 0 16 Nov 2021
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space Jiehong Lin Hongyang Li Ke Chen Jiangbo Lu K. Jia 3DPC 19 20 0 14 Nov 2021
Understanding the Generalization Benefit of Model Invariance from a Data Perspective Sicheng Zhu Bang An Furong Huang 8 25 0 10 Nov 2021
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 32 23 0 09 Nov 2021
Equivariant Deep Dynamical Model for Motion Prediction Bahar Azari Deniz Erdoğmuş 25 1 0 02 Nov 2021
SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du He Zhang Yuanqi Du Qi Meng Wei-Neng Chen Bin Shao Tie-Yan Liu 50 79 0 26 Oct 2021
Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups David M. Knigge David W. Romero Erik J. Bekkers 16 30 0 25 Oct 2021
Learning Partial Equivariances from Data David W. Romero Suhas Lohit 19 26 0 19 Oct 2021
Equivariant Finite Normalizing Flows A. Bose Marcus A. Brubaker I. Kobyzev DRL 26 8 0 16 Oct 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 24 16 0 15 Oct 2021
Augmenting Imitation Experience via Equivariant Representations Dhruv Sharma Ali Kuwajerwala Florian Shkurti 19 2 0 14 Oct 2021
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? M. Farrell Blake Bordelon Shubhendu Trivedi C. Pehlevan 13 5 0 14 Oct 2021
Multi-Agent MDP Homomorphic Networks Elise van der Pol H. V. Hoof F. Oliehoek Max Welling AI4CE 46 28 0 09 Oct 2021
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter Rob D. Hesselink Elise van der Pol Erik J. Bekkers Max Welling 17 229 0 06 Oct 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy Robin G. Walters Yanchen Liu Dashun Wang Rose Yu AI4CE 78 81 0 15 Sep 2021
Nonlinearities in Steerable SO(2)-Equivariant CNNs Daniel Franzen Michael Wand 30 3 0 14 Sep 2021
Topographic VAEs learn Equivariant Capsules Thomas Anderson Keller Max Welling BDL 36 38 0 03 Sep 2021
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods Tobias Alt Karl Schrader Joachim Weickert Pascal Peter M. Augustin 22 4 0 31 Aug 2021
Convolutional Filtering and Neural Networks with Non Commutative Algebras Alejandro Parada-Mayorga Landon Butler Alejandro Ribeiro 27 10 0 23 Aug 2021
Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney W. Kuo D. Rossinelli G. Schulz R. Wenger S. Hieber B. Müller V. Kurtcuoglu 16 8 0 04 Aug 2021
6DCNN with roto-translational convolution filters for volumetric data processing Dmitrii Zhemchuzhnikov Ilia Igashov Sergei Grudinin 3DPC 22 2 0 26 Jul 2021
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems Michael Muehlebach Michael I. Jordan 26 18 0 17 Jul 2021
USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems G. Tong 31 5 0 15 Jul 2021
Universal approximation and model compression for radial neural networks I. Ganev Twan van Laarhoven Robin G. Walters 19 8 0 06 Jul 2021
Steerable Partial Differential Operators for Equivariant Neural Networks Erik Jenner Maurice Weiler 15 27 0 18 Jun 2021
Training or Architecture? How to Incorporate Invariance in Neural Networks Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller 3DPC OOD 17 9 0 18 Jun 2021
Rotation Invariant Graph Neural Networks using Spin Convolutions Muhammed Shuaibi Adeesh Kolluru Abhishek Das Aditya Grover Anuroop Sriram Zachary W. Ulissi C. L. Zitnick AI4CE 10 67 0 17 Jun 2021
Equivariant Networks for Pixelized Spheres Mehran Shakerinava Siamak Ravanbakhsh 3DPC 23 19 0 12 Jun 2021
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales Ylva Jansson T. Lindeberg 11 23 0 11 Jun 2021
Group Equivariant Subsampling Jin Xu Hyunjik Kim Tom Rainforth Yee Whye Teh 23 21 0 10 Jun 2021
Exploiting Learned Symmetries in Group Equivariant Convolutions A. Lengyel J. C. V. Gemert 24 5 0 09 Jun 2021
DISCO: accurate Discrete Scale Convolutions Ivan Sosnovik A. Moskalev A. Smeulders 18 31 0 04 Jun 2021
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities Oliver T. Unke Mihail Bogojeski M. Gastegger Mario Geiger Tess E. Smidt Klaus-Robert Muller 23 86 0 04 Jun 2021
Steerable 3D Spherical Neurons Pavlo Melnyk M. Felsberg Mårten Wadenbäck 3DPC LLMSV 21 5 0 02 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 21 433 0 02 Jun 2021
Symmetry-via-Duality: Invariant Neural Network Densities from Parameter-Space Correlators Anindita Maiti Keegan Stoner James Halverson 23 20 0 01 Jun 2021
Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry Zhuoran Qiao Anders S. Christensen Matthew Welborn F. Manby Anima Anandkumar Thomas F. Miller 16 74 0 31 May 2021
Geometric Deep Learning and Equivariant Neural Networks Jan E. Gerken J. Aronsson Oscar Carlsson H. Linander F. Ohlsson Christoffer Petersson Daniel Persson MLT 13 66 0 28 May 2021
FILTRA: Rethinking Steerable CNN by Filter Transform Bo-wen Li Qili Wang G. Lee 11 4 0 25 May 2021
Protein sequence-to-structure learning: Is this the end(-to-end revolution)? É. Laine Stephan Eismann A. Elofsson Sergei Grudinin OOD 3DV 17 34 0 16 May 2021
Homogeneous vector bundles and $G$ -equivariant convolutional neural networks J. Aronsson 24 24 0 12 May 2021
Learning Gradient Fields for Molecular Conformation Generation Chence Shi Shitong Luo Minkai Xu Jian Tang DiffM AI4CE 31 210 0 09 May 2021
Vector Neurons: A General Framework for SO(3)-Equivariant Networks Congyue Deng Or Litany Yueqi Duan A. Poulenard Andrea Tagliasacchi Leonidas J. Guibas 3DPC 111 315 0 25 Apr 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 76 185 0 19 Apr 2021
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph Chen Cai Nikolaos N. Vlassis Lucas Magee R. Ma Zeyu Xiong B. Bahmani T. Wong Yusu Wang WaiChing Sun 22 16 0 12 Apr 2021
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs Zhengyang Shen Tiancheng Shen Zhouchen Lin Jinwen Ma 13 18 0 08 Apr 2021
Equivariant Point Network for 3D Point Cloud Analysis Haiwei Chen Shichen Liu Weikai Chen Hao Li 3DPC 19 99 0 25 Mar 2021
Equivariant Filters for Efficient Tracking in 3D Imaging Daniel Moyer Esra Abaci Turk P. E. Grant W. Wells Polina Golland 3DPC 11 18 0 18 Mar 2021
Iterative SE(3)-Transformers F. Fuchs E. Wagstaff Justas Dauparas Ingmar Posner 25 17 0 26 Feb 2021