Frontiers20d
A framework for computer-aided high performance titanium alloy design based on machine learning
Firstly, a proprietary dataset was constructed for titanium alloy materials using feature design and a combination of unsupervised and supervised feature engineering methods. Secondly, six machine ...
IEEE22d
Self-Supervised Learning and Nearest Neighbors for Out-Of-Distribution Modulation Classification
In this letter, we consider OOD scenarios with varying carrier frequency offset and varying sampling frequency and propose a new self-supervised method to improve the robustness of modulation ...
C&EN25d
Structural Similarity, Activity, and Toxicity of Mycotoxins: Combining Insights from Unsupervised and Supervised Machine Learning Algorithms
Coimbra Chemistry Centre, Department of Chemistry, Institute of Molecular Sciences (IMS), Faculty of Sciences and Technology, University of Coimbra, R. Larga 2, 3004-535 Coimbra, Portugal ...
GitHub25d
self-supervised-learning
Theory, Experiments, and Dataset for our newly proposed Deep Learning method for Cycle Consistency and Semantics Aware Self-Supervised Framework for Unpaired LDR ↔ HDR Image Translation ...
eLife26d
Semantical and Geometrical Protein Encoding Toward Enhanced Bioactivity and Thermostability
An illustration of ProtSSN that extracts the semantical and ... ProtSSN is designed for protein engineering with a self-supervised learning scheme. The model is capable of conducting zero-shot variant ...
Frontiers2y
Decoding Intracranial EEG With Machine Learning: A Systematic Review
The review revealed that supervised algorithms were most ... ML and DL in order to compare algorithm performance. Unsupervised learning made up a minority of articles found (6/107, 6%). An ...