A Meta-Analysis Approach for Feature Selection in Network Traffic Research. - Daniel C. Ferreira; Félix Iglesias Vázquez; Gernot Vormayr; Maximilian Bachl; Tanja Zseby (Reproducibility@SIGCOMM, 2017)

Cocoa: Congestion Control Aware Queuing. - Maximilian Bachl; Joachim Fabini; Tanja Zseby (BS, 2019)

Walling up Backdoors in Intrusion Detection Systems. - Maximilian Bachl; Alexander Hartl; Joachim Fabini; Tanja Zseby (Big-DAMA@CoNEXT, 2019)

Rax: Deep Reinforcement Learning for Congestion Control. - Maximilian Bachl; Tanja Zseby; Joachim Fabini (ICC, 2019)

City-GAN: Learning architectural styles using a custom Conditional GAN architecture. - Maximilian Bachl; Daniel C. Ferreira (CoRR, 2019)

Explainability and Adversarial Robustness for RNNs. - Alexander Hartl; Maximilian Bachl; Joachim Fabini; Tanja Zseby (BigDataService, 2020)

SparseIDS: Learning Packet Sampling with Reinforcement Learning. - Maximilian Bachl; Fares Meghdouri; Joachim Fabini; Tanja Zseby (CNS, 2020)

EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion Detection. - Fares Meghdouri; Maximilian Bachl; Tanja Zseby (CSNet, 2020)

LFQ: Online Learning of Per-flow Queuing Policies using Deep Reinforcement Learning. - Maximilian Bachl; Joachim Fabini; Tanja Zseby (LCN, 2020)

Optimizing Congestion Control Through Fair Queuing Detection. - Maximilian Bachl; Joachim Fabini; Tanja Zseby (CoRR, 2020)

A flow-based IDS using Machine Learning in eBPF. - Maximilian Bachl; Joachim Fabini; Tanja Zseby (CoRR, 2021)

Fair Queuing Aware Congestion Control. - Maximilian Bachl (CoRR, 2022)