A new deep clustering method, scDAEC, combines two autoencoders and multi-head attention to untangle noisy single-cell RNA ...

Researchers at the University of Oklahoma combined density functional theory calculations with graph neural networks to ...

Alibaba's Qwen-Image-2.1 is a 7B open-weight model unifying image generation, editing, and native RGBA transparency under research license.

The model learns to reconstruct clean images from noisy inputs through a symmetric encoder-decoder architecture: Encoder — convolutional + pooling layers compress the input into a compact latent ...

A factory floor has 200 vibration sensors streaming data every second. Storing and processing all 200 channels in real time is expensive and slow. But most signals are correlated: when one motor ...

Low-field MRI is gaining interest, especially in low-resource settings, due to its low cost, portability, small footprint, and low power consumption. However, it suffers from significant noise, ...

Materials functionalities may be associated with atomic-level structural dynamics occurring on the millisecond timescale. However, the capability of electron microscopy to image structures with high ...

本项目是基于PyTorch框架实现的堆叠去噪卷积自编码器（Stacked Denoising Convolutional Autoencoder）。自编码器是一种无监督学习模型，用于数据的特征学习和降维。堆叠去噪卷积自编码器通过逐层学习 ...

机器学习之线性回归（Machine Learning about Linear Regression） 本文系统介绍线性回归基础与进阶应用，涵盖一元及多元线性回归、最小二乘法、均方误差（MSE）与决定系数（R²）评估指标。 阅读详情 ...