Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network

24 June 2018

Papers citing "Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network"

50 / 183 papers shown

Title
Data efficiency and extrapolation trends in neural network interatomic potentials Joshua A Vita Daniel Schwalbe-Koda 34 16 0 12 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
How Jellyfish Characterise Alternating Group Equivariant Neural Networks Edward Pearce-Crump 21 4 0 24 Jan 2023
Flattening-Net: Deep Regular 2D Representation for 3D Point Cloud Analysis Qijian Zhang Junhui Hou Y. Qian Yiming Zeng Juyong Zhang Ying He 3DPC 40 24 0 17 Dec 2022
Brauer's Group Equivariant Neural Networks Edward Pearce-Crump AI4CE 13 15 0 16 Dec 2022
Lorentz group equivariant autoencoders Zichun Hao Raghav Kansal Javier Mauricio Duarte N. Chernyavskaya BDL DRL AI4CE 23 23 0 14 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
Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data Leevi Kerkelä K. Seunarine F. Szczepankiewicz C. Clark DiffM MedIm 20 2 0 17 Nov 2022
Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism Zimu Li Zihan Pengmei Han Zheng Erik H. Thiede Junyu Liu Risi Kondor 27 2 0 14 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
A tradeoff between universality of equivariant models and learnability of symmetries Vasco Portilheiro 27 2 0 17 Oct 2022
Theory for Equivariant Quantum Neural Networks Quynh T. Nguyen Louis Schatzki Paolo Braccia Michael Ragone Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo 27 88 0 16 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
Representation Theory for Geometric Quantum Machine Learning Michael Ragone Paolo Braccia Quynh T. Nguyen Louis Schatzki Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo AI4CE 26 73 0 14 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
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 31 16 0 29 Sep 2022
In Search of Projectively Equivariant Networks Georg Bökman Axel Flinth Fredrik Kahl 37 0 0 29 Sep 2022
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions Jeremy Ocampo Matthew Alexander Price Jason D. McEwen 21 13 0 27 Sep 2022
Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments Jaspreet Singh Chandan Singh 14 5 0 22 Sep 2022
Multi-Task Mixture Density Graph Neural Networks for Predicting Cu-based Single-Atom Alloy Catalysts for CO2 Reduction Reaction Chen Liang Bo-Lan Wang Shaogang Hao Guangyong Chen Pheng-Ann Heng Xiaolong Zou 50 1 0 15 Sep 2022
A Feedforward Unitary Equivariant Neural Network P. Ma Terence Chan 26 4 0 25 Aug 2022
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs Zhengyang Shen T. Hong Qi She Jinwen Ma Zhouchen Lin MedIm 11 7 0 07 Aug 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 42 370 0 05 Aug 2022
e3nn: Euclidean Neural Networks Mario Geiger Tess E. Smidt 35 173 0 18 Jul 2022
Spherical Channels for Modeling Atomic Interactions C. L. Zitnick Abhishek Das Adeesh Kolluru Janice Lan Muhammed Shuaibi Anuroop Sriram Zachary W. Ulissi Brandon M. Wood 79 58 0 29 Jun 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 80 213 0 23 Jun 2022
Approximate Equivariance SO(3) Needlet Convolution Kai Yi Jialin Chen Yu Guang Wang Bingxin Zhou Pietro Lio' Yanan Fan J. Hamann 11 4 0 17 Jun 2022
An Algorithm for the SE(3)-Transformation on Neural Implicit Maps for Remapping Functions Yijun Yuan A. Nüchter 18 9 0 17 Jun 2022
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces Yinshuang Xu Jiahui Lei Edgar Dobriban Kostas Daniilidis 23 19 0 16 Jun 2022
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation Haohan Wang Zeyi Huang Xindi Wu Eric P. Xing OOD 19 15 0 04 Jun 2022
Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling Mingxing Xu Chenglin Li Wenrui Dai Siheng Chen Junni Zou P. Frossard H. Xiong 32 2 0 31 May 2022
Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups Sho Sonoda Isao Ishikawa Masahiro Ikeda 30 9 0 30 May 2022
VectorAdam for Rotation Equivariant Geometry Optimization Selena Ling Nicholas Sharp Alec Jacobson 23 16 0 26 May 2022
VNT-Net: Rotational Invariant Vector Neuron Transformers Hedi Zisling Andrei Sharf 3DPC 24 1 0 19 May 2022
What is an equivariant neural network? Lek-Heng Lim Bradley J. Nelson BDL FedML MLT 32 22 0 15 May 2022
Low Dimensional Invariant Embeddings for Universal Geometric Learning Nadav Dym S. Gortler 21 39 0 05 May 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters Tycho F. A. van der Ouderaa David W. Romero Mark van der Wilk 24 33 0 14 Apr 2022
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics Albert Musaelian Simon L. Batzner A. Johansson Lixin Sun Cameron J. Owen M. Kornbluth Boris Kozinsky 22 425 0 11 Apr 2022
Equivariance Discovery by Learned Parameter-Sharing Raymond A. Yeh Yuan-Ting Hu M. Hasegawa-Johnson A. Schwing FedML 24 14 0 07 Apr 2022
Symmetry Group Equivariant Architectures for Physics A. Bogatskiy S. Ganguly Thomas Kipf Risi Kondor David W. Miller ... Jan T. Offermann M. Pettee P. Shanahan C. Shimmin S. Thais AI4CE 19 27 0 11 Mar 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 31 44 0 22 Feb 2022
Equivariance versus Augmentation for Spherical Images Jan E. Gerken Oscar Carlsson H. Linander F. Ohlsson Christoffer Petersson Daniel Persson 3DPC 22 14 0 08 Feb 2022
Improving the Sample-Complexity of Deep Classification Networks with Invariant Integration M. Rath A. P. Condurache 25 8 0 08 Feb 2022
FourierNet: Shape-Preserving Network for Henle's Fiber Layer Segmentation in Optical Coherence Tomography Images Selahattin Cansiz Cem Kesim Sevval Nur Bektas Zeynep Kulali M. Hasanreisoğlu C. Gunduz-Demir 33 9 0 17 Jan 2022
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ansätze Han Zheng Zimu Li Junyu Liu Sergii Strelchuk Risi Kondor 50 54 0 14 Dec 2021
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids Peter Bjørn Jørgensen Arghya Bhowmik 16 36 0 01 Dec 2021
Deformation Robust Roto-Scale-Translation Equivariant CNNs Liyao (Mars) Gao Guang Lin Wei-wei Zhu 20 8 0 22 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 53 79 0 26 Oct 2021