HexaConv

6 March 2018

Papers citing "HexaConv"

22 / 22 papers shown

Title
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 48 2 0 06 Oct 2023
CB2: Collaborative Natural Language Interaction Research Platform Jacob Sharf Mustafa Omer Gul Yoav Artzi LLMAG 35 1 0 14 Mar 2023
Deep Neural Networks with Efficient Guaranteed Invariances M. Rath Alexandru Paul Condurache 18 4 0 02 Mar 2023
Continual Learning for Instruction Following from Realtime Feedback Alane Suhr Yoav Artzi 31 17 0 19 Dec 2022
Energy Reconstruction in Analysis of Cherenkov Telescopes Images in TAIGA Experiment Using Deep Learning Methods E. Gres A. P. Kryukov 25 4 0 16 Nov 2022
Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments Jaspreet Singh Chandan Singh 27 5 0 22 Sep 2022
E2PN: Efficient SE(3)-Equivariant Point Network Minghan Zhu Maani Ghaffari W. A. Clark Huei Peng 3DPC 29 18 0 11 Jun 2022
Domain-informed neural networks for interaction localization within astroparticle experiments Shixiao Liang A. Higuera C. Peters Venkat Roy W. Bajwa H. Shatkay C. Tunnell 27 7 0 15 Dec 2021
Deformation Robust Roto-Scale-Translation Equivariant CNNs Liyao (Mars) Gao Guang Lin Wei-wei Zhu 30 8 0 22 Nov 2021
Resampling and super-resolution of hexagonally sampled images using deep learning Dylan Flaute R. Hardie Hamed Elwarfalli SupR 37 1 0 03 Nov 2021
Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior Noriyuki Kojima Alane Suhr Yoav Artzi 27 24 0 10 Aug 2021
Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions Qi Xie Qian Zhao Zongben Xu Deyu Meng 27 19 0 30 Jul 2021
Commutative Lie Group VAE for Disentanglement Learning Xinqi Zhu Chang Xu Dacheng Tao CoGe DRL 40 22 0 07 Jun 2021
A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory R. Abbasi M. Ackermann J. Adams J. Aguilar M. Ahlers ... Zifei Shan J. Yáñez S. Yoshida T. Yuan Zhe Zhang 44 46 0 27 Jan 2021
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes P. Holderrieth M. Hutchinson Yee Whye Teh BDL 38 30 0 25 Nov 2020
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images S. Graham David B. A. Epstein Nasir M. Rajpoot 24 88 0 06 Apr 2020
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs P. D. Haan Maurice Weiler Taco S. Cohen Max Welling 104 127 0 11 Mar 2020
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis Maxime W. Lafarge Erik J. Bekkers J. Pluim R. Duits M. Veta MedIm 27 74 0 20 Feb 2020
Hexagonal Image Processing in the Context of Machine Learning: Conception of a Biologically Inspired Hexagonal Deep Learning Framework Tobias Schlosser Michael Friedrich Danny Kowerko 14 15 0 25 Nov 2019
B-Spline CNNs on Lie Groups Erik J. Bekkers AI4CE 37 129 0 26 Sep 2019
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 310 0 05 Nov 2018
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data Maurice Weiler Mario Geiger Max Welling Wouter Boomsma Taco S. Cohen 3DPC 45 495 0 06 Jul 2018