Even weak ocean models can provide valuable information for environmental forecasts, study shows

Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing ...

How a machine learning engineer built a churn prediction model that transformed a subscription platform’s retention strategy

A subscription technology platform with over 100,000 users was losing customers each month despite having access to ...
acm.org

From Prediction to Intervention: Integrating Counterfactual Reasoning into AI Decision-Making

The analysts working on AI projects have a crucial question: How will the interventions brought about by the AI cause the desired outcomes? To date, only about 20% of companies have managed to scale ...
GitHub

Covariance Data Frames for Predictive M/EEG Pipelines

For this purpose, coffeine uses DataFrames to handle multiple covariance matrices alongside scalar features. Vectorization and model composition functions are provided that handle composition of valid ...
GitHub

Predictive Biomarker Modeling Framework (PBMF)

The PBMF (Publised in Cancer cell ) is an automated neural network framework based on contrastive learning. This general-purpose framework explores potential predictive biomarkers in a systematic and ...
SciELO

Predictive Modeling of Rheological Behavior in Semisolid Pharmaceutical Formulations Using Computational Tools.

Topical treatments for skin conditions offer significant benefits, yet understanding the rheological characteristics of semi-solid formulations is crucial, as they directly influence treatment ...
IEEE

Lyapunov-Based Model Predictive Control of Nonlinear Systems Subject to Data Losses

Abstract: In this work, we focus on model predictive control of nonlinear systems subject to data losses. The motivation for considering this problem is provided by wireless networked control systems ...