Nils Strodthoff
Orcid: 0000-0003-4447-0162
According to our database1,
Nils Strodthoff
authored at least 36 papers
between 2017 and 2024.
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Bibliography
2024
IEEE J. Biomed. Health Informatics, April, 2024
SonicGuard Sensor - A Multichannel Acoustic Sensor for Long-Term Monitoring of Abdominal Sounds Examined through a Qualification Study.
Sensors, March, 2024
Trans. Mach. Learn. Res., 2024
CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models.
CoRR, 2024
Assessing the importance of long-range correlations for deep-learning-based sleep staging.
CoRR, 2024
Explaining deep learning for ECG analysis: Building blocks for auditing and knowledge discovery.
Comput. Biol. Medicine, 2024
2023
Towards Quantitative Precision for ECG Analysis: Leveraging State Space Models, Self-Supervision and Patient Metadata.
IEEE J. Biomed. Health Informatics, November, 2023
Comput. Biol. Medicine, September, 2023
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees.
Trans. Mach. Learn. Res., 2023
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models.
Trans. Mach. Learn. Res., 2023
From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology.
Medical Image Anal., 2023
Cardiac and extracardiac discharge diagnosis prediction from emergency department ECGs using deep learning.
CoRR, 2023
S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models.
CoRR, 2023
Insights Into the Inner Workings of Transformer Models for Protein Function Prediction.
CoRR, 2023
2022
Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models.
CoRR, 2022
Comput. Biol. Medicine, 2022
Artif. Intell., 2022
Proceedings of the Computing in Cardiology, 2022
2021
IEEE J. Biomed. Health Informatics, 2021
Inferring Respiratory and Circulatory Parameters from Electrical Impedance Tomography With Deep Recurrent Models.
IEEE J. Biomed. Health Informatics, 2021
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy.
CoRR, 2021
Predicting the Binding of SARS-CoV-2 Peptides to the Major Histocompatibility Complex with Recurrent Neural Networks.
CoRR, 2021
2020
CoRR, 2020
USMPep: universal sequence models for major histocompatibility complex binding affinity prediction.
BMC Bioinform., 2020
Bioinform., 2020
2019
IEEE J. Sel. Areas Commun., 2019
Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling.
CoRR, 2019
Proceedings of the Pattern Recognition, 2019
2018
Detecting and interpreting myocardial infarctions using fully convolutional neural networks.
CoRR, 2018
Proceedings of the IEEE Globecom Workshops, 2018
2017