Image Reconstruction with AutoEncoder This project demonstrates image reconstruction using an AutoEncoder model on the MNIST dataset. The AutoEncoder compresses input images into a smaller latent ...

An autoencoder is a type of artificial neural network designed to learn efficient representations of the input data, typically by compressing the input into a lower-dimensional latent space and then ...

Therefore, this paper proposes a dual-adaptive fusion multi-view clustering method based on graph autoencoder. It utilizes multi-view encoders and decoders to encode and reconstruct inputs separately.

This paper proposes a learning-based approach for reconstruction of global illumination with very low sampling budgets (as low as 1 spp) at interactive rates. At 1 sample per pixel (spp), the Monte ...

Automotive radar has been extensively utilized in cars for many years as an essential sensor, primarily due to its robustness in extreme weather conditions, its capacity to measure Doppler information ...

Multi-view feature learning has garnered much attention recently since many real world data are comprised of different representations or views. How to explore the consensus structure and eliminate ...

Serial-autoencoder for personalized recommendation. Higher Education Press . Journal Frontiers of Computer Science DOI 10.1007/s11704-023-2441-1 ...