Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
IEEE

Learning With Partial-Label and Unlabeled Data: Contrastive With Negative Example Separation

Abstract: Semi-Supervised Partial Label Learning (SSPLL) is an important branch of weakly supervised learning, where the data consists of both partial label examples and unlabeled ones. In SSPLL, the ...
IEEE

Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package

Abstract: Spectral pixels are often a mixture of the pure spectra of the materials, called endmembers, due to the low spatial resolution of hyperspectral sensors, double scattering, and intimate ...
GitHub

This is the second repo for the book "LLVM Code Generation". This will be linked to the main repo for this title.

The purpose of this repository is to offer a step by step implementation of an LLVM backend from scratch. Use the begin_chXX end_chXX tags to follow what we do in the related chapters. This particular ...
GitHub

verl: Volcano Engine Reinforcement Learning for LLMs

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.
C&EN

Accelerated Screening of Zeolites for Methanol-to-Propylene Conversion Using Machine Learning with Interpretable Selectivity Function

College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, P. R. China Center for Innovative Research in Synthetic Chemistry and Resource ...