47 citations · 48 across the 4 of their papers we have counts for
4 papers
BenchECG and xECG: a benchmark and baseline for ECG foundation models
Riccardo Lunelli, Angus Nicolson, Samuel Martin Pröll +3
Electrocardiograms (ECGs) are inexpensive, widely used, and well-suited to deep learning. Recently, interest has grown in developing foundation models for ECGs - models that genera…
Noisier2Inverse: Self-Supervised Learning for Image Reconstruction with Correlated Noise
Nadja Gruber, Johannes Schwab, Markus Haltmeier +3
We propose Noisier2Inverse, a correction-free self-supervised deep learning approach for general inverse problems. The proposed method learns a reconstruction function without the…
EchoDFKD: Data-Free Knowledge Distillation for Cardiac Ultrasound Segmentation using Synthetic Data
Grégoire Petit, Nathan Palluau, Axel Bauer +1
The application of machine learning to medical ultrasound videos of the heart, i.e., echocardiography, has recently gained traction with the availability of large public datasets.…
Quantum optimization via four-body Rydberg gates
Clemens Dlaska, Kilian Ender, Glen Bigan Mbeng +3
There is a large ongoing research effort towards obtaining a quantum advantage in the solution of combinatorial optimization problems on near-term quantum devices. A particularly p…