On the Utility of Partially Labeled Data for Classification of Microarray Data. - Ludwig Lausser; Florian Schmid; Hans A. Kestler (PSL, 2011)

Three Transductive Set Covering Machines. - Florian Schmid; Ludwig Lausser; Hans A. Kestler (GfKl, 2012)

Linear Contrast Classifiers in High-Dimensional Spaces. - Florian Schmid; Ludwig Lausser; Hans A. Kestler (ANNPR, 2014)

Unlabeling data can improve classification accuracy. - Ludwig Lausser; Florian Schmid; Matthias Schmid; Hans A. Kestler (Pattern Recognit. Lett., 2014)

Sputnik: ad hoc distributed computation. - Gunnar Völkel; Ludwig Lausser; Florian Schmid; Johann M. Kraus; Hans A. Kestler (Bioinform., 2015)

Interpretable Classifiers in Precision Medicine: Feature Selection and Multi-class Categorization. - Lyn-Rouven Schirra; Florian Schmid; Hans A. Kestler; Ludwig Lausser (ANNPR, 2016)

BiTrinA - multiscale binarization and trinarization with quality analysis. - Christoph Müssel; Florian Schmid; Tamara J. Blätte; Martin Hopfensitz; Ludwig Lausser; Hans A. Kestler (Bioinform., 2016)

GiANT: gene set uncertainty in enrichment analysis. - Florian Schmid; Matthias Schmid; Christoph Müssel; J. Eric Sträng; Christian Buske; Lars Bullinger; Johann M. Kraus; Hans A. Kestler (Bioinform., 2016)

Robust and interpretable classification models for molecular high-throughput data. - Florian Schmid (2016)

Rank-based classifiers for extremely high-dimensional gene expression data. - Ludwig Lausser; Florian Schmid; Lyn-Rouven Schirra; Adalbert F. X. Wilhelm; Hans A. Kestler (Adv. Data Anal. Classif., 2018)

Line scanning fMRI reveals earlier onset of optogenetically evoked BOLD response in rat somatosensory cortex as compared to sensory stimulation. - Franziska Albers; Florian Schmid; Lydia Wachsmuth; Cornelius Faber (NeuroImage, 2018)

FoSIL - Offensive language classification of German tweets combining SVMs and deep learning techniques. - Florian Schmid; Justine Thielemann; Anna Mantwill; Jian Xi; Dirk Labudde; Michael Spranger (KONVENS, 2019)

Carbon monofilament electrodes for unit recording and functional MRI in same subjects. - Miguel R. Chuapoco; ManKin Choy; Florian Schmid; Ben A. Duffy; Hyun Joo Lee; Jin Hyung Lee (NeuroImage, 2019)

Learning General Audio Representations With Large-Scale Training of Patchout Audio Transformers. - Khaled Koutini; Shahed Masoudian; Florian Schmid; Hamid Eghbal-zadeh; Jan Schlüter; Gerhard Widmer (HEAR@NeurIPS, 2021)

Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification. - Florian Schmid; Shahed Masoudian; Khaled Koutini; Gerhard Widmer (DCASE, 2022)

Simulation Based Approach for Reconfiguration and Ramp Up Scenario Analysis in Factory Planning. - Florian Schmid; Jan Schneidewind; Tobias Wild; Stefan Galka; Lukas Schuhegger; Tobias Vogl (WSC, 2022)

Oral History auf dem Weg zu Big Data: menschliche und maschinelle Annotation lebensgeschichtlicher Interviews im Vergleich. - Nils Egger; Lina Franken; Dennis Möbus; Florian Schmid (DHd, 2023)

Device-Robust Acoustic Scene Classification via Impulse Response Augmentation. - Tobias Morocutti; Florian Schmid; Khaled Koutini; Gerhard Widmer (EUSIPCO, 2023)

Low-Complexity Audio Embedding Extractors. - Florian Schmid; Khaled Koutini; Gerhard Widmer (EUSIPCO, 2023)

Efficient Large-Scale Audio Tagging Via Transformer-to-CNN Knowledge Distillation. - Florian Schmid; Khaled Koutini; Gerhard Widmer (ICASSP, 2023)

Domain Transfer for Surface Defect Detection using Few-Shot Learning on Scarce Data. - Felix Gerschner; Jonas Paul; Lukas Schmid; Nico Barthel; Victor Gouromichos; Florian Schmid; Martin Atzmueller; Andreas Theissler (INDIN, 2023)

Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge. - Florian Schmid; Paul Primus; Toni Heittola; Annamaria Mesaros; Irene Martín-Morató; Khaled Koutini; Gerhard Widmer (CoRR, 2024)

Improving Audio Spectrogram Transformers for Sound Event Detection Through Multi-Stage Training. - Florian Schmid; Paul Primus; Tobias Morocutti; Jonathan Greif; Gerhard Widmer (CoRR, 2024)

Estimated Audio-Caption Correspondences Improve Language-Based Audio Retrieval. - Paul Primus; Florian Schmid; Gerhard Widmer (CoRR, 2024)

Dynamic Convolutional Neural Networks as Efficient Pre-Trained Audio Models. - Florian Schmid; Khaled Koutini; Gerhard Widmer (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

Effective Pre-Training of Audio Transformers for Sound Event Detection. - Florian Schmid; Tobias Morocutti; Francesco Foscarin; Jan Schlüter; Paul Primus; Gerhard Widmer (ICASSP, 2025)

Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification. - Tobias Morocutti; Florian Schmid; Khaled Koutini; Gerhard Widmer (CoRR, 2025)

Exploring Performance-Complexity Trade-Offs in Sound Event Detection. - Tobias Morocutti; Florian Schmid; Jonathan Greif; Francesco Foscarin; Gerhard Widmer (CoRR, 2025)

Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 Challenge. - Florian Schmid; Paul Primus; Toni Heittola; Annamaria Mesaros; Irene Martín-Morató; Gerhard Widmer (CoRR, 2025)

TACOS: Temporally-aligned Audio CaptiOnS for Language-Audio Pretraining. - Paul Primus; Florian Schmid; Gerhard Widmer (CoRR, 2025)

On Temporal Guidance and Iterative Refinement in Audio Source Separation. - Tobias Morocutti; Jonathan Greif; Paul Primus; Florian Schmid; Gerhard Widmer (CoRR, 2025)