Spherical cnns iclr
WebApr 16, 2024 · Researchers at the University of Amsterdam proposed Spherical Convolutional Neural Networks (CNNs) which can analyze spherical images, a technique … WebJan 30, 2024 · We demonstrate the computational efficiency, numerical accuracy, and effectiveness of spherical CNNs applied to 3D model recognition and atomization energy …
Spherical cnns iclr
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WebSuch a high computational cost often prohibits the use of strictly equivariant spherical CNNs. We develop two new strictly equivariant layers with reduced complexity OpCL4q … WebFeb 22, 2024 · Efficient Generalized Spherical CNNs (ICLR 2024) - YouTube A brief overview of our paper on Efficicient Generalized Spherical CNNs accepted for ICLR 2024. Talk by …
WebJan 7, 2024 · Abstract and Figures We present an efficient convolution kernel for Convolutional Neural Networks (CNNs) on unstructured grids using parameterized differential operators while focusing on... WebSep 6, 2024 · In this paper, we model 3D-data with spherical functions valued in { {\mathbb {R}}}^n and introduce a novel equivariant convolutional neural network with spherical inputs (Fig. 2 illustrates the equivariance). We clarify the difference between convolution that has spherical outputs and correlation that has outputs in the rotation group \mathbf ...
WebWe propose a definition for the spherical cross-correlation that is both expressive and rotation-equivariant. The spherical correlation satisfies a generalized Fourier theorem, which allows us to compute it efficiently using a generalized (non-commutative) Fast Fourier Transform (FFT) algorithm. WebApr 12, 2024 · Balanced Spherical Grid for Egocentric View Synthesis Changwoon Choi · Sang Min Kim · Young Min Kim pCON: Polarimetric Coordinate Networks for Neural Scene Representations ... LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs Yukang Chen · Jianhui Liu · Xiangyu Zhang · XIAOJUAN QI · Jiaya Jia
WebThe new spherical CNNs are constructed with the novel convolution with spin-weighted functions, enabling both expressive and efficient CNNs on non-Euclidean domains. The spin-weighted spherical harmonics have applications in gravitational radiation and electromagnetic theory.
WebJan 30, 2024 · We propose a definition for the spherical cross-correlation that is both expressive and rotation-equivariant. The spherical correlation satisfies a generalized … imported commoditiesWebFeb 15, 2024 · TL;DR: We introduce Spherical CNNs, a convolutional network for spherical signals, and apply it to 3D model recognition and molecular energy regression. Abstract : … imported chicken from chinaWebEfficient Generalized Spherical CNNs. Publication Type: Conference . Authors: Cobb OJ, Wallis CGR, Mavor-Parker AN, Marignier A, Price MA, d'Avezac M, McEwen JD. Publication date: 04/05/2024. Published proceedings: ICLR 2024 - 9th International Conference on Learning Representations. Status: Published. Name of conference: imported dates hyderabadWebSep 27, 2024 · No existing spherical convolutional neural network (CNN) framework is both computationally scalable and rotationally equivariant. Continuous approaches capture rotational equivariance but are often prohibitively computationally demanding. Discrete approaches offer more favorable computational performance but at the cost of … imported christmas tree ornamentsWebWe model 3D data with multi- valued spherical functions and we propose a novel spherical convolutional network that implements exact convolutions on the sphere by realizing them in the spherical harmonic domain. Resulting filters have local sym- metry and are localized by enforcing smooth spectra. imported consumer goodsWebConvolutional neural networks (CNNs) constructed natively on the sphere have been developed recently and shown to be highly effective for the analysis of spherical data. … imported componentsWebApr 12, 2024 · A brief overview of our paper on Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions accepted for ICLR 2024. Talk by Jason McEwen ( … imported exotic pets