Image, trained entirely on Huawei chips, as Beijing moves to block Nvidia H200 imports in a push for AI self-reliance.

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

一个全面、工程化、基于 PyTorch 的现代扩散模型实现库。 支持 DDPM、DDIM、CFG 等多种扩散算法，集成 UNet、DiT、DiM 等先进主干网络。 提供分布式训练、EMA、实验追踪、完整评估指标，开箱即用。

Abstract: Respiratory patterns are important indicators of human health, and using AI models to analyze channel state information (CSI) for non-contact respiratory detection shows great potential.

Medical imaging has become an essential tool for identifying and treating neurological conditions. Traditional deep learning (DL) models have made tremendous advances in neuroimaging analysis; however ...

Deep learning models have become indispensable in medical image analysis, particularly for detecting and classifying ocular diseases. Automated diagnostic systems are promising to improve accuracy and ...

Objective: To develop and test an interpretable machine learning model that combines clinical data, radiomics, and deep learning features using different regions of interest (ROI) from magnetic ...

We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...

Xavier Rubio-Campillo does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations ...