12 citations · 20 across the 3 of their papers we have counts for
3 papers
Federated Few-Shot Learning for Epileptic Seizure Detection Under Privacy Constraints
Ekaterina Sysoykova, Bernhard Anzengruber-Tanase, Michael Haslgrubler +2
Many deep learning approaches have been developed for EEG-based seizure detection; however, most rely on access to large centralized annotated datasets. In clinical practice, EEG d…
Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl +7
Language models for biological and chemical sequences enable crucial applications such as drug discovery, protein engineering, and precision medicine. Currently, these language mod…
Context-enriched molecule representations improve few-shot drug discovery
Johannes Schimunek, Philipp Seidl, Lukas Friedrich +4
A central task in computational drug discovery is to construct models from known active molecules to find further promising molecules for subsequent screening. However, typically o…