Explainable Deep Learning

Explainable Deep Learning: A Field Guide for the Uninitiated - arXiv

This article offers a field guide to explore the space of explainable deep learning aimed at those uninitiated in the field.

Chapter 2 - Explainable deep learning: concepts, methods, and new ...

In short, the idea of this approach is to map something which we do not know how to explain to a form (i.e., we “neuralize” it by constructing an equivalent ...

Explainable Deep Neural Networks - Towards Data Science

In this work we propose a new way to make Deep Neural Networks more comprehensible when converting data encoded into practical knowledge. In each hidden layer ...

Explainable Deep Learning: : A Field Guide for the Uninitiated

Deep neural networks (DNNs) are an indispensable machine learning tool despite the difficulty of diagnosing what aspects of a model's input drive its ...

Explainability in Deep Learning: Demystifying the Black Box - Medium

This article explores the importance of explainability in deep learning, the challenges it poses, and the techniques used to improve model interpretability.

Explainable Deep Learning: A Field Guide for the Uninitiated

This article offers a field guide to explore the space of explainable deep learning for those in the AI/ML field who are uninitiated.

Explainability Methods for Deep Learning Neural Networks - Nature

This collection welcomes submissions on explainability techniques for deep learning neural networks, encompassing diverse neural architectures and ensuring ...

Explainable artificial intelligence - Wikipedia

Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), either refers to an artificial intelligence (AI) ...

What are explainable neural networks? : r/deeplearning - Reddit

The field is also sometimes called “mechanistic interpretability” or just “interpretability.” It is neuroscience or psychology for the ...

Explainable artificial intelligence (XAI) in deep learning-based ...

A framework of XAI criteria is introduced to classify deep learning-based medical image analysis methods. Papers on XAI techniques in medical image analysis are ...

Explainable Deep Learning: A Visual Analytics Approach with ...

This study aims to enhance the explainability of DL models through visual analytics (VA) and human-in-the-loop (HITL) principles.

Explainable Deep Learning Models in Medical Image Analysis - PMC

A review of the current applications of explainable deep learning for different medical imaging tasks is presented here.

Principles and Practice of Explainable Machine Learning - Frontiers

In this report, we focus specifically on data-driven methods—machine learning (ML) and pattern recognition models in particular—so as to survey and distill the ...

Explainable Deep Learning for False Information Identification

We propose a computational framework that helps machine learning for false information identification (FII) understand the connection between a claim.

Explainable Deep Neural Networks for Multivariate Time Series ...

Roy Assaf, Anika Schumann ... We demonstrate that CNN deep neural networks can not only be used for making predictions based on multivariate time series data, but ...

Explainable Deep Learning: : A Field Guide for the Uninitiated

This article offers a field guide to explore the space of explainable deep learning for those in the AI/ML field who are uninitiated.

XAI Tutorial: Explainability OF Deep Neural Networks - YouTube

Deep Neural Networks are often treated as black boxes. This talk will focus on some of the modern methods of explainability for DNNs and ...

Explainable AI: A Review of Machine Learning Interpretability Methods

This study focuses on machine learning interpretability methods; more specifically, a literature review and taxonomy of these methods are presented.

What is Explainable AI (XAI)? - IBM

Explainable artificial intelligence (XAI) allows human users to comprehend and trust the results and output created by machine learning algorithms.

Explainable deep learning models for healthcare - CDSS 3 - Coursera

Program local explainability methods for deep learning such as CAM and GRAD-CAM. Understand axiomatic attributions for deep learning networks.