Find a refurbished Xperia deal that's better for your wallet and the planet. Refurbished Xperia guaranteed to work like new for less than buying new.
- Refurbished Goods
Check out our selection
of-exceptionally priced products.
- Refurbished Super Market
Shop Our Refurbished Market-At
Back Market Today.
- Back Market
Your Refurbished (Super) Market.
Find Out More About Back Market.
- Our Services
Find Out More About Our Services
And How We Can Help You.
- Accessories
iPhone, AirPods, Apple Watch, iPad
and Apple Watch Accessories.
- About Us
Our Mission Is To Restore Trust And
Desire For Refurbished Devices.
- Refurbished Goods
Search results
Oct 30, 2023 · View a PDF of the paper titled Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions, by Luca Longo and 18 other authors View PDF Abstract: As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount.
Nov 1, 2023 · Existing XAI work can be categorized in various ways, including XAI applications, multidisciplinary method fusion, and explainability by internal functionality modification, among others. The following subsection goes through the reviewed literature. 2.1. Previous studies. XAI has the potential to be extremely beneficial to the AI research ...
Jun 1, 2024 · 1. Introduction. The field of Explainable AI (XAI) has grown significantly over the past few years. It has evolved from being a niche research topic within the larger field of Artificial Intelligence (AI) [1], [2], [3] to becoming a highly active field of research, with a large number of theoretical contributions, empirical studies, and reviews being proposed every year [4], [5].
Abstract. Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper highlights the advancements in ...
- XAI - An eXplainability toolbox for machine learning
- 0.1.0
- What do we mean by eXplainable AI?
- Installation
- Usage
XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contains various tools that enable for analysis and evaluation of data and models. The XAI library is maintained by The Institute for Ethical AI & ML, and it was developed based on the 8 principles for Responsible Machine Learning.
You can find the documentation at https://ethicalml.github.io/xai/index.html. You can also check out our talk at Tensorflow London where the idea was first conceived - the talk also contains an insight on the definitions and principles in this library.
If you want to see a fully functional demo in action clone this repo and run the Example Jupyter Notebook in the Examples folder.
We see the challenge of explainability as more than just an algorithmic challenge, which requires a combination of data science best practices with domain-specific knowledge. The XAI library is designed to empower machine learning engineers and relevant domain experts to analyse the end-to-end solution and identify discrepancies that may result in sub-optimal performance relative to the objectives required. More broadly, the XAI library is designed using the 3-steps of explainable machine learning, which involve 1) data analysis, 2) model evaluation, and 3) production monitoring.
We provide a visual overview of these three steps mentioned above in this diagram:
The XAI package is on PyPI. To install you can run:
Alternatively you can install from source by cloning the repo and running:
1) Data Analysis
With XAI you can identify imbalances in the data. For this, we will load the census dataset from the XAI library.
2) Model Evaluation
We are able to also analyse the interaction between inference results and input features. For this, we will train a single layer deep learning model.
Oct 30, 2023 · Similarly, 2.2 demonstrates the large and increasing number of applications of XAI methods, techniques, and tools and their utility in real-world scenarios. 2.1 XAI T rends, Advances, and ...
People also ask
What is Xai 2.0?
What is explainable AI (XAI)?
What does Xai stand for?
What are Xai aspects?
Jul 1, 2021 · Thus, our model serves to identify interdisciplinary potential and is aimed to establish a common ground for different disciplines involved in XAI. Overall, the current paper is intended for an interdisciplinary readership interested in XAI. 1.2. A conceptual model of the relation between explainability approaches and stakeholders' desiderata
