Convolutional Neural Networks for Movement Prediction in Videos. - Alexander Warnecke; Timo Lüddecke; Florentin Wörgötter (GCPR, 2017)

Don't Paint It Black: White-Box Explanations for Deep Learning in Computer Security. - Alexander Warnecke; Daniel Arp; Christian Wressnegger; Konrad Rieck (CoRR, 2019)

Detecting Various Road Damage Types in Global Countries Utilizing Faster R-CNN. - Felix Kortmann; Kevin Talits; Pascal Fassmeyer; Alexander Warnecke; Nicolas Meier; Jens Heger; Paul Drews; Burkhardt Funk (IEEE BigData, 2020)

Evaluating Explanation Methods for Deep Learning in Security. - Alexander Warnecke; Daniel Arp; Christian Wressnegger; Konrad Rieck (EuroS&P, 2020)

Live Demonstration: Passive Sensor Setup for Road Condition Monitoring. - Felix Kortmann; Julin Horstkötter; Alexander Warnecke; Nicolas Meier; Jens Heger; Burkhardt Funk; Paul Drews (IEEE SENSORS, 2020)

Creating Value from in-Vehicle Data: Detecting Road Surfaces and Road Hazards. - Felix Kortmann; Yi-Chen Hsu; Alexander Warnecke; Nicolas Meier; Jens Heger; Burkhardt Funk; Paul Drews (ITSC, 2020)

Applying Quarter-Vehicle Model Simulation for Road Elevation Measurements Utilizing the Vehicle Level Sensor. - Felix Kortmann; Malte Rodeheger; Alexander Warnecke; Nicolas Meier; Jens Heger; Burkhardt Funk; Paul Drews (VTC Fall, 2020)

Explaining Graph Neural Networks for Vulnerability Discovery. - Tom Ganz; Martin Härterich; Alexander Warnecke; Konrad Rieck (AISec@CCS, 2021)

Concept of a Cloud State Modeling System for Lead-Acid Batteries: Theory and Prototyping. - Felix Kortmann; Daniel Brieske; Pia Piekarek; Julian Eckstein; Alexander Warnecke; Paul Drews; Dirk Uwe Sauer (ICEIC, 2021)

TagVet: Vetting Malware Tags using Explainable Machine Learning. - Lukas Pirch; Alexander Warnecke; Christian Wressnegger; Konrad Rieck (EuroSec@EuroSys, 2021)

State of Health Estimation of Lithium-Ion Batteries for Dynamic Driving Profiles Based on Feature Extraction from Battery Relaxation Time Using Machine Learning. - Nitika Ghosh; Akhil Garg 003; Alexander Warnecke; Bijaya K. Panigrahi (IECON, 2022)

Dos and Don'ts of Machine Learning in Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (USENIX Security Symposium, 2022)

Machine Unlearning of Features and Labels. - Alexander Warnecke; Lukas Pirch; Christian Wressnegger; Konrad Rieck (NDSS, 2023)

Evil from Within: Machine Learning Backdoors through Hardware Trojans. - Alexander Warnecke; Julian Speith; Jan-Niklas Möller; Konrad Rieck; Christof Paar (CoRR, 2023)

Lessons Learned on Machine Learning for Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (IEEE Secur. Priv., 2023)

Evil from Within: Machine Learning Backdoors Through Dormant Hardware Trojans. - Alexander Warnecke; Julian Speith; Jan-Niklas Möller; Konrad Rieck; Christof Paar (ACSAC, 2024)

Battery Health Prediction Using Commixtured Multi-Feature Selection and Transfer Learning. - Nitika Ghosh; Akhil Garg 003; Alexander Warnecke (ISGT Asia, 2024)

Manipulating Feature Visualizations with Gradient Slingshots. - Dilyara Bareeva; Marina M.-C. Höhne; Alexander Warnecke; Lukas Pirch; Klaus-Robert Müller; Konrad Rieck; Kirill Bykov (CoRR, 2024)

Security viewpoints on explainable machine learning. - Alexander Warnecke (2024)

Pitfalls in Machine Learning for Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (Commun. ACM, 2024)