Nature

Causal Inference and Bayesian Network Learning

The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...
VentureBeat

Why machine learning struggles with causality

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More When you look at a baseball player hitting the ball, you can make ...
News Medical

Advancing gene regulatory network inference with causal discovery and graph neural networks

Gene regulatory networks (GRNs) depict the regulatory mechanisms of genes within cellular systems as a network, offering vital insights for understanding cell processes and molecular interactions that ...
Princeton University

CITP Lecture: Amanda Coston - Responsible Machine Learning through the Lens of Causal Inference

Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...
Harvard Business School

Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning

Stern, Ariel Dora, and W. Nicholson Price, II. "Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning." Biostatistics 21, no. 2 ...
Drinks

Panasonic in big data: theme innovation strategy

Panasonic had 14 patents in big data during Q4 2023. Panasonic Holdings Corp filed patents in Q4 2023 for a system using statistical background subtraction to generate causal inference machine ...
Drinks

Panasonic in artificial intelligence: theme innovation strategy

Panasonic had 107 patents in artificial intelligence during Q4 2023. Panasonic Holdings Corp filed patents in Q4 2023 for methods and systems related to information processing, causal inference ...