B-Spline CNNs on Lie Groups

26 September 2019

Papers citing "B-Spline CNNs on Lie Groups"

50 / 95 papers shown

Title
Diffusion for Multi-Embodiment Grasping Roman Freiberg Alexander Qualmann Ngo Anh Vien Gerhard Neumann 29 3 0 24 Oct 2024
On the VC dimension of deep group convolutional neural networks Anna Sepliarskaia S. Langer Johannes Schmidt-Hieber MLT 28 0 0 21 Oct 2024
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups Zakhar Shumaylov Peter Zaika James Rowbottom Ferdia Sherry Melanie Weber Carola-Bibiane Schönlieb 34 1 0 03 Oct 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 44 2 0 18 Sep 2024
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations Andrzej Perzanowski Tony Lindeberg 45 1 0 17 Sep 2024
Adaptive Sampling for Continuous Group Equivariant Neural Networks Berfin Inal Gabriele Cesa 35 0 0 13 Sep 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 39 4 0 23 Aug 2024
Scale-Translation Equivariant Network for Oceanic Internal Solitary Wave Localization Zhang Wan Shuo Wang Xudong Zhang 36 0 0 18 Jun 2024
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields David M. Knigge David R. Wessels Riccardo Valperga Samuele Papa J. Sonke E. Gavves Erik J. Bekkers AI4CE 36 4 0 10 Jun 2024
Neural Isometries: Taming Transformations for Equivariant ML Thomas W. Mitchel Michael Taylor Vincent Sitzmann 28 0 0 29 May 2024
Approximation properties relative to continuous scale space for hybrid discretizations of Gaussian derivative operators Tony Lindeberg 34 2 0 08 May 2024
Covariant spatio-temporal receptive fields for spiking neural networks Jens Egholm Pedersen Jorg Conradt Tony Lindeberg 32 3 0 01 May 2024
Geometric Generative Models based on Morphological Equivariant PDEs and GANs El Hadji S. Diop Thierno Fall Alioune Mbengue Mohamed Daoudi GAN 33 1 0 22 Mar 2024
Neural Operators with Localized Integral and Differential Kernels Miguel Liu-Schiaffini Julius Berner Boris Bonev Thorsten Kurth Kamyar Azizzadenesheli A. Anandkumar 58 18 0 26 Feb 2024
Hierarchical Invariance for Robust and Interpretable Vision Tasks at Larger Scales Shuren Qi Yushu Zhang Chao Wang Zhihua Xia Xiaochun Cao Jian Weng 16 1 0 23 Feb 2024
Optimal Transport on the Lie Group of Roto-translations Daan Bon Gautam Pai Gijs Bellaard Olga Mula R. Duits OT 16 0 0 23 Feb 2024
Clifford-Steerable Convolutional Neural Networks Maksim Zhdanov David Ruhe Maurice Weiler Ana Lucic Johannes Brandstetter Patrick Forré 47 12 0 22 Feb 2024
Discrete approximations of Gaussian smoothing and Gaussian derivatives Tony Lindeberg 24 12 0 19 Nov 2023
Unified theory for joint covariance properties under geometric image transformations for spatio-temporal receptive fields according to the generalized Gaussian derivative model for visual receptive fields Tony Lindeberg 16 7 0 17 Nov 2023
Affine Invariance in Continuous-Domain Convolutional Neural Networks A. Mohaddes Johannes Lederer 18 1 0 13 Nov 2023
Truly Scale-Equivariant Deep Nets with Fourier Layers Md Ashiqur Rahman Raymond A. Yeh 47 8 0 06 Nov 2023
Lie Group Decompositions for Equivariant Neural Networks Mircea Mironenco Patrick Forré AI4CE 23 7 0 17 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
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 40 1 0 06 Oct 2023
Fast, Expressive SE $(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space Erik J. Bekkers Sharvaree P. Vadgama Rob D. Hesselink P. A. V. D. Linden David W. Romero 13 24 0 04 Oct 2023
Latent Space Symmetry Discovery Jianke Yang Nima Dehmamy Robin G. Walters Rose Yu 30 12 0 29 Sep 2023
Geometry of Linear Neural Networks: Equivariance and Invariance under Permutation Groups Kathlén Kohn Anna-Laura Sattelberger V. Shahverdi 25 3 0 24 Sep 2023
Scale-Rotation-Equivariant Lie Group Convolution Neural Networks (Lie Group-CNNs) Weizheng Qiao Yang Xu Hui Li 26 0 0 12 Jun 2023
$E(2)$ -Equivariant Vision Transformer Renjun Xu Kaifan Yang Ke Liu Fengxiang He ViT MDE 19 9 0 11 Jun 2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance Mircea Petrache Shubhendu Trivedi 33 22 0 27 May 2023
Higher Order Gauge Equivariant CNNs on Riemannian Manifolds and Applications Gianfranco Cortés Yue Yu R. Chen Melissa S. Armstrong David E Vaillancourt B. Vemuri 29 1 0 26 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 26 34 0 18 May 2023
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural network Wenzhao Zhao Barbara D. Wichtmann Steffen Albert Angelika Maurer F. G. Zollner Ulrike Attenberger Jurgen Hesser 22 1 0 17 May 2023
An Exploration of Conditioning Methods in Graph Neural Networks Yeskendir Koishekenov Erik J. Bekkers AI4CE 35 3 0 03 May 2023
Scale-Equivariant Deep Learning for 3D Data Thomas Wimmer Vladimir Golkov H. Dang Moritz Zaiss Andreas K. Maier Daniel Cremers 3DPC MedIm 18 5 0 12 Apr 2023
Scale-Equivariant UNet for Histopathology Image Segmentation Yi-Lun Yang S. Dasmahapatra S. Mahmoodi 20 11 0 10 Apr 2023
Covariance properties under natural image transformations for the generalized Gaussian derivative model for visual receptive fields T. Lindeberg 21 11 0 17 Mar 2023
Deep Neural Networks with Efficient Guaranteed Invariances M. Rath A. P. Condurache 16 4 0 02 Mar 2023
Empowering Networks With Scale and Rotation Equivariance Using A Similarity Convolution Zikai Sun T. Blu 16 6 0 01 Mar 2023
Generative Adversarial Symmetry Discovery Jianke Yang Robin G. Walters Nima Dehmamy Rose Yu GAN 19 22 0 01 Feb 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
Equivariant Light Field Convolution and Transformer Yinshuang Xu Jiahui Lei Kostas Daniilidis ViT 19 0 0 30 Dec 2022
VC dimensions of group convolutional neural networks P. Petersen A. Sepliarskaia VLM 19 7 0 19 Dec 2022
Implicit Convolutional Kernels for Steerable CNNs Maksim Zhdanov Nico Hoffmann Gabriele Cesa 29 5 0 12 Dec 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks Arash Behboodi Gabriele Cesa Taco S. Cohen 48 17 0 24 Oct 2022
Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE Alireza Nasiri Tristan Bepler DRL 14 12 0 24 Oct 2022
LieGG: Studying Learned Lie Group Generators A. Moskalev A. Sepliarskaia Ivan Sosnovik A. Smeulders 28 22 0 09 Oct 2022
Analysis of (sub-)Riemannian PDE-G-CNNs Gijs Bellaard Daan Bon Gautam Pai B. Smets R. Duits AI4CE 28 12 0 03 Oct 2022
Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments Jaspreet Singh Chandan Singh 14 5 0 22 Sep 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 39 370 0 05 Aug 2022