Abstract: With the explosive growth of data volume, distributed machine learning has become the mainstream approach for training deep neural networks. However, distributed machine learning incurs ...
Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions
Abstract: Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction. However, they usually suffer from two critical ...
You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...
Bhattacharjee, S. S. and Petersen, I. R., Analysis of the Whiplash gradient descent dynamics, Asian J. Control (2023), 1–14, DOI 10.1002/asjc.3153. This file contains live MATLAB projects and Simulink ...
What began with a focus on weather forecasting has evolved toward addressing errors in scientific modeling. In the collaborative environment of the Penn State Institute for Computational and Data ...
We use the PU-Net dataset for training, you can refer to https://github.com/yulequan/PU-Net to download the .h5 dataset file, which can be directly used in this ...
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