Nature

Modelling the urban acoustic environment using land use-based gradient boosting

Long-standing research on the relationship between the urban acoustic environment (AE) and human health demonstrates the harmful effects of environmental noise. Meanwhile, an increasing number of ...
Nature

A dual enhanced stochastic gradient descent method with dynamic momentum and step size adaptation for improved optimization performance

In modern machine learning, optimization algorithms are crucial; they steer the training process by skillfully navigating through complex, high-dimensional loss landscapes. Among these, stochastic ...
GitHub

Fast Python Collaborative Filtering for Implicit Datasets.

Alternating Least Squares as described in the papers Collaborative Filtering for Implicit Feedback Datasets and Applications of the Conjugate Gradient Method for Implicit Feedback Collaborative ...
ahajournals.org

Toward Dynamic Risk Prediction of Outcomes After Coronary Artery Bypass Graft: Improving Risk Prediction With Intraoperative Events Using Gradient Boosting

Intraoperative data may improve models predicting postoperative events. We evaluated the effect of incorporating intraoperative variables to the existing preoperative model on the predictive ...
PNAS

DeepTFactor: A deep learning-based tool for the prediction of transcription factors

Identification of transcription factors (TFs) is a starting point for the analysis of transcriptional regulatory systems of organisms. Here, we report the development of DeepTFactor, a deep ...
GitHub

POT: Python Optimal Transport

This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. OT barycenters (Wasserstein and GW) ...