Frontiers

Climate and Environmental Influences on Maternal, Newborn and Child Health in Africa: Physical and Social Pathways, knowledge translation and intervention

Environmental and climatic conditions induce risk across from the prenatal to early childhood periods. Increasingly frequent ...
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 ...

insitro Validates AI-Enabled POSH Platform in Nature Communications, Bridging Critical Gap in Drug Discovery

AI therapeutics company built on causal biology, today announced the publication of research in Nature Communications validating its POSH (Pooled Optical Screening in Human cells) platform. The study ...
C&EN

Green Bond Issuance and Carbon Emissions: Can Causal Machine Learning Inform Forward-Looking Policy Decisions?

Green bonds finance projects intended to deliver environmental benefits, including reductions in greenhouse gas emissions. However, evidence that municipal green bond issuance lowers local carbon ...
EurekAlert!

Causal machine learning reveals the impact of renewables on electricity prices

Comparison of raw correlations (dashed) and causal effects (solid) of wind on UK day-ahead prices. Lines show the price change (GBP/MWh) from +1 GWh of predicted wind for the delivery hour across ...
Forbes

The Rise Of The AI Inference Economy

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...
VentureBeat

Together AI's ATLAS adaptive speculator delivers 400% inference speedup by learning from workloads in real-time

Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads. Speculators are smaller AI models that work ...
San Diego Reader

Rethinking Machine Learning: Stuart Frost Makes the Case for Causal AI in Manufacturing

The manufacturing landscape is evolving rapidly, with intelligent systems increasingly promising to boost efficiency, quality, and overall competitiveness. Traditional machine learning (ML) has ...
Scientific Research Publishing

Estimating Average and Heterogeneous Effects of Special Education: A Causal Machine Learning Perspective ()

Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the causal ...
Frontiers

Beyond just correlation: causal machine learning for the microbiome, from prediction to health policy with econometric tools

The human microbiome is increasingly recognized as a key mediator of health and disease, yet translating microbial associations into actionable interventions remains challenging. This review ...
IEEE

Integrating Machine Learning and Observational Causal Inference for Enhanced Spectral and Energy Efficiency in Wireless Networks

Abstract: Ensuring transparency and explainability in Artificial Intelligence (AI)/Machine Learning (ML) models is crucial for their effective deployment in wireless networks. This paper addresses the ...