Nature

Explainable machine learning by SEE-Net: closing the gap between interpretable models and DNNs

Deep Neural Networks (DNNs) have achieved remarkable accuracy for numerous applications, yet their complexity often renders the explanation of predictions a challenging task. This complexity contrasts ...
Nature

Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19

A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine ...
Healio

Explainable machine learning can improve efforts to diagnose CKD early

Please provide your email address to receive an email when new articles are posted on . Explainable machine learning can offer accurate diagnoses and identify causes of chronic kidney disease in early ...
InfoQ

Ethical Machine Learning with Explainable AI and Impact Analysis

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Bloomberg L.P.

Accurately assessing liquidity with explainable machine learning models

Being able to explain how machine learning models work has been a point of contention since the technology’s inception. Bloomberg is set to release further empirical metrics, at the end of this year, ...

Global Leadership In Explainable AI And Intelligent Financial Technologies: The Growing Impact Of Shekar Vollem

Shekar Vollem, a Senior Software Engineer, researcher, inventor, peer reviewer, and technology leader whose work spans ...
InfoWorld

Explainable AI explained

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...
EurekAlert!

‘Explainable AI’ can efficiently detect AR/VR cybersickness

COLUMBIA, Mo. – Exposure to an augmented reality (AR) or virtual reality (VR) environment can cause people to experience cybersickness — a special type of motion sickness with symptoms ranging from ...
Harvard Business School

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning ...
Electronic Design

Explainable AI for Anomaly Detection

What is explainable AI (XAI)? What are some of the use cases for XAI? What are the technology requirements for implementing XAI? Anomaly detection is the process of identifying when something deviates ...
Frontiers

AI-Driven Monitoring of the Terrestrial Water Cycle: Evapotranspiration, Soil Moisture, and Drought Under Climate Change

The terrestrial water cycle is a fundamental component of Earth's climate system, governing the exchange of water between land surfaces and the atmosphere.