GitHub

Xiaohan-Chen/transfer-learning-fault-diagnosis-pytorch

For further introductions to transfer learning in bearing fault diagnosis, please read our paper. And if you find this repository useful and use it in your works, please cite our paper, thank you~: ...
The Robot Report

We know how to build smarter robots. Now, we need to learn smarter ways to test them

Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...
IEEE

A Survey on Self-Supervised Learning: Algorithms, Applications, and Future Trends

Abstract: Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data can be ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

Semi-Supervised Learning Algorithm for Identifying High-Priority Drug–Drug Interactions ...

Abstract: Identifying drug-drug interactions (DDIs) is a critical enabler for reducing adverse drug events and improving patient safety. Generating proper DDI alerts during prescribing workflow has ...
EurekAlert!

A review of machine learning advances in reliability-based design, integrity assessment ...

A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...