SoK: Explainable Machine Learning for Computer Security Applications

Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors

A Fast Multi-objective Evolutionary Approach for Designing Large-Scale Optical Mode Sorter

Detecting moments of distraction during meditation practice based on changes in the EEG signal

Data-Driven Support Vector Machine to Predict Thin-Walled Tube Energy Absorbers Behavior

Improving Adaptive Learning Models Using Prosodic Speech Features

Generation of design allowables on the open hole tensile strength of composite laminates using sensitivity analysis and uncertainty quantification framework

MLTK01: A Prototyping Toolkit for Tangible Learning Things

Fusion of Radar Data Domains for Human Activity Recognition in Assisted Living

Interpretable neural network with limited weights for constructing simple and explainable HI using SHM data

Classifying EEG Signals of Mind-Wandering Across Different Styles of Meditation

When Machine Learning Models Leak: An Exploration of Synthetic Training Data

Label-Only Membership Inference Attack against \\Node-Level Graph Neural Networks

Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling

MLSmellHound: A Context-Aware Code Analysis Tool

Comparative Evaluation of Machine Learning Inference Machines on Edge-class Devices

AI supported noise analyses for structure design requirements definition

ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility

Using Machine Learning to Quantify the Robustness of Network Controllability

Demonstrating a Bayesian Online Learning for Energy-Aware Resource Orchestration in vRANs