Uncertainty Quantification

Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks

Improving Differential Evolution through Bayesian Hyperparameter Optimization

Trinity: Trust, Resilience and Interpretability of Machine Learning Models

Toward Safe Decision-Making via Uncertainty Quantification in Machine Learning

Computational Intelligence in Uncertainty Quantification for Learning Controland Differential Games

Ursabench: Comprehensive benchmarking of approximate bayesian inference methods for deep neural networks

On uncertainty and robustness in large-scale intelligent data fusion systems

Generalized bayesian posterior expectation distillation for deep neural networks

Better call surrogates: A hybrid evolutionary algorithm for hyperparameter optimization

Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification