xxAI - Beyond Explainable AI
portes grátis
xxAI - Beyond Explainable AI
International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers
Mueller, Klaus-Robert; Fong, Ruth; Goebel, Randy; Moon, Taesup; Holzinger, Andreas; Samek, Wojciech
Springer International Publishing AG
04/2022
397
Mole
Inglês
9783031040825
15 a 20 dias
623
Descrição não disponível.
Editorial.- xxAI - Beyond explainable Artificial Intelligence.- Current Methods and Challenges.- Explainable AI Methods - A Brief Overview.- Challenges in Deploying Explainable Machine Learning.- Methods for Machine Learning Models.- CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations.- New Developments in Explainable AI.- A Rate-Distortion Framework for Explaining Black-box Model Decisions.- Explaining the Predictions of Unsupervised Learning Models.- Towards Causal Algorithmic Recourse.- Interpreting Generative Adversarial Networks for Interactive Image Generation.- XAI and Strategy Extraction via Reward Redistribution.- Interpretable, Verifiable, and Robust Reinforcement Learning via Program Synthesis.- Interpreting and improving deep-learning models with reality checks.- Beyond the Visual Analysis of Deep Model Saliency.- ECQ^2: Quantization for Low-Bit and Sparse DNNs.- A whale's tail - Finding the right whale in an uncertain world.- Explainable Artificial Intelligence in Meteorology and Climate Science: Model fine-tuning, calibrating trust and learning new science.- An Interdisciplinary Approach to Explainable AI.-Varieties of AI Explanations under the Law - From the GDPR to the AIA, and beyond.- Towards Explainability for AI Fairness.- Logic and Pragmatics in AI Explanation.
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Computer Science;Informatics;Conference Proceedings;Research;Applications;Open Access
Editorial.- xxAI - Beyond explainable Artificial Intelligence.- Current Methods and Challenges.- Explainable AI Methods - A Brief Overview.- Challenges in Deploying Explainable Machine Learning.- Methods for Machine Learning Models.- CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations.- New Developments in Explainable AI.- A Rate-Distortion Framework for Explaining Black-box Model Decisions.- Explaining the Predictions of Unsupervised Learning Models.- Towards Causal Algorithmic Recourse.- Interpreting Generative Adversarial Networks for Interactive Image Generation.- XAI and Strategy Extraction via Reward Redistribution.- Interpretable, Verifiable, and Robust Reinforcement Learning via Program Synthesis.- Interpreting and improving deep-learning models with reality checks.- Beyond the Visual Analysis of Deep Model Saliency.- ECQ^2: Quantization for Low-Bit and Sparse DNNs.- A whale's tail - Finding the right whale in an uncertain world.- Explainable Artificial Intelligence in Meteorology and Climate Science: Model fine-tuning, calibrating trust and learning new science.- An Interdisciplinary Approach to Explainable AI.-Varieties of AI Explanations under the Law - From the GDPR to the AIA, and beyond.- Towards Explainability for AI Fairness.- Logic and Pragmatics in AI Explanation.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
