ABSTRACT: With the deepening of oil and gas exploration, the exploration targets have gradually shifted from structural oil and gas reservoirs to lithological oil and gas reservoirs. The fluvial ...

Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.

Abstract: A fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a ...

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...

Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...