Frontiers

Causal Machine Learning for Treatment Selection and Outcome Optimization in Mood Disorders

Mood disorders represent a major global burden and are characterized by substantial heterogeneity in symptom profiles, treatment response, and clinical ...
IEEE

Network Deconvolution for Causal Inference in Production Flows

Abstract: This thesis introduces a methodology based on network deconvolution to uncover causal relationships within production systems. The approach separates direct and indirect effects to ...
GitHub

Nonlinear multilevel spline modeling for Python.

Nonlinear relationships are common in applied research, especially in education, health, and economics. While Python provides statsmodels for mixed-effects models and patsy for spline construction, ...
GitHub

Missing official FastAPI-based lightweight REST inference example for OpenVINO Python API

OpenVINO provides powerful Python APIs for model conversion and inference, as well as OpenVINO Model Server (OVMS) for production deployments. However, there is currently no official lightweight REST ...
IEEE

The Causal Inference of Bayesian Network Based on Improved IDA Algorithm

Abstract: At present, the IDA algorithm is a commonly used method for estimating causal effects between variables from observational data. In the IDA algorithm, the PC algorithm is first used to ...