IEEE

Conv4Rec: A 1-by-1 Convolutional Autoencoder for User Profiling Through Joint Analysis of Implicit and Explicit Feedback

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 ...
IEEE

Fault Detection Method for Power Conversion Circuits Using Thermal Image and Convolutional Autoencoder

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 commercial power ...
GitHub

vae-cnn

PyTorch-based pipeline that trains a convolutional variational autoencoder on cat images, optionally tunes hyperparameters with Ray Tune, and samples new images by fitting a Gaussian Mixture Model in ...
C&EN

DeepAIPs-SFLA: Deep Convolutional Model for Prediction of Anti-Inflammatory Peptides Using Binary Pattern Decomposition of Novel Multiview Descriptors with an SFLA Approach

Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China ...
GitHub

Layer Attribution for Convolutional Networks

Hi @bilalsal @NarineK @sarahtranfb @vivekmig @aobo-y, First of all, thank you for the amazing work on Captum! I'm currently exploring the capabilities of Captum for analyzing a convolutional neural ...