Reinforcement Learning Approach to Active Learning for Image Classification. - Thorben Werner (CoRR, 2021)

Open Set Recognition for Time Series Classification. - Tolga Akar; Thorben Werner; Vijaya Krishna Yalavarthi; Lars Schmidt-Thieme (PAKDD (2), 2022)

When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development. - Nghia Duong-Trung; Stefan Born; Jong Woo Kim; Marie-Therese Schermeyer; Katharina Paulick; Maxim Borisyak; Ernesto C. Martínez; Mariano Nicolás Cruz Bournazou; Thorben Werner; Randolf Scholz; Lars Schmidt-Thieme; Peter Neubauer (CoRR, 2022)

Towards Comparable Knowledge Distillation in Semantic Image Segmentation. - Onno Niemann; Christopher Vox; Thorben Werner (PKDD/ECML Workshops (4), 2023)

A Cross-Domain Benchmark for Active Learning. - Thorben Werner; Johannes Burchert; Maximilian Stubbemann; Lars Schmidt-Thieme (NeurIPS, 2024)

Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training. - Johannes Burchert; Thorben Werner; Vijaya Krishna Yalavarthi; Diego Coello de Portugal; Maximilian Stubbemann; Lars Schmidt-Thieme (CoRR, 2024)

Bayesian Active Learning By Distribution Disagreement. - Thorben Werner; Lars Schmidt-Thieme (CoRR, 2025)