IEEE

CiiNet: Self-Iterative Performance Optimization for Dynamic Networks Based on Causal Inference and Interpretable Evaluation

Abstract: Causal inference and root cause analysis play a crucial role in network performance evaluation and optimization by identifying critical parameters and explaining how the configuration ...
Frontiers

Integrative causal inference and predictive modeling reveal the iron-related gene SLC17A4 as a key biomarker in chronic rhinosinusitis

Department of Otorhinolaryngology, The First Hospital of China Medical University, Shenyang, Liaoning, China Purpose: To investigate whether iron metabolism exerts a causal influence on chronic ...
IEEE

Causal Inference Via Style Bias Deconfounding for Domain Generalization

Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...
GitHub

CausalInferenceLab/awesome-causal-inference-python

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GitHub

Causal Inference and Discovery in Python

What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...
eLife

Correlation detection as a stimulus computable account for audiovisual perception, causal inference, and saliency maps in mammals

Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of ...
ahajournals.org

Abstract 4368647: Improving Center Performance Assessment in Congenital Heart Surgery Through Causal Inference Weighting Approaches

Background: Traditional congenital heart surgery quality assessments rely on indirect standardization via regression, which can be complicated by heterogeneity in case-mix, surgical volume, and low ...
publichealth.jhu

The promise and pitfalls of integrating data for causal inference, with application to mental health treatment

Please join the Department of Epidemiology Center for Clinical Trials and Evidence Synthesis (CCTES) and Center for Drug Safety and Effectiveness (CDSE) in welcoming Elizabeth Stuart, PhD, AM, Chair ...
marktechpost

What is Asyncio? Getting Started with Asynchronous Python and Using Asyncio in an AI Application with an LLM

In many AI applications today, performance is a big deal. You may have noticed that while working with Large Language Models (LLMs), a lot of time is spent waiting—waiting for an API response, waiting ...
Frontiers

Correlation does not equal causation: the imperative of causal inference in machine learning models for immunotherapy

1 Department of Orthopedics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China 2 Department of Pharmacy, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, ...