Logic Explained Networks

The Computational Complexity of Understanding Binary Classifier Decisions

(2021) Stephan Waeldchen et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers

(2021) Stefano Melacci et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Adversarial Learning Targeting Deep Neural Network Classification: A Comprehensive Review of Defenses Against Attacks

(2020) David J. Miller et al.   PROCEEDINGS OF THE IEEE

Machine Learning Interpretability: A Survey on Methods and Metrics

(2019) Diogo V. Carvalho et al.   Electronics

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Model selection and overfitting

(2016) Jake Lever et al.   NATURE METHODS

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

(2015) Benjamin Letham et al.   Annals of Applied Statistics

Foundations of Support Constraint Machines

(2015) Giorgio Gnecco et al.   NEURAL COMPUTATION

Changing concepts of working memory

(2014) Wei Ji Ma et al.   NATURE NEUROSCIENCE

Constraint Verification With Kernel Machines

(2013) M. Gori et al.   IEEE Transactions on Neural Networks and Learning Systems

Unsupervised Learning by Minimal Entropy Encoding

(2012) S. Melacci et al.   IEEE Transactions on Neural Networks and Learning Systems

Multiparameter Intelligent Monitoring in Intensive Care II: A public-access intensive care unit database*

(2011) Mohammed Saeed et al.   CRITICAL CARE MEDICINE

Distilling Free-Form Natural Laws from Experimental Data

(2009) Michael Schmidt et al.   SCIENCE