default search action
Nils Strodthoff
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j17]Patrick Wagner, Temesgen Mehari
, Wilhelm Haverkamp
Explaining deep learning for ECG analysis: Building blocks for auditing and knowledge discovery. Comput. Biol. Medicine 176: 108525 (2024) - [j16]Zahra Mansour, Verena N. Uslar
SonicGuard Sensor - A Multichannel Acoustic Sensor for Long-Term Monitoring of Abdominal Sounds Examined through a Qualification Study. Sensors 24(6): 1843 (2024) - [j15]Temesgen Mehari
ECG Feature Importance Rankings: Cardiologists Vs. Algorithms. IEEE J. Biomed. Health Informatics 28(4): 2014-2024 (2024) - [j14]Stefan Bluecher, Johanna Vielhaben, Nils Strodthoff:
Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks. Trans. Mach. Learn. Res. 2024 (2024) - [i32]Stefan Blücher, Johanna Vielhaben, Nils Strodthoff:
Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks. CoRR abs/2401.06654 (2024) - [i31]Tiezhi Wang, Nils Strodthoff:
Assessing the importance of long-range correlations for deep-learning-based sleep staging. CoRR abs/2402.17779 (2024) - [i30]Juan Miguel Lopez Alcaraz, Nils Strodthoff:
CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models. CoRR abs/2405.15871 (2024) - [i29]Juan Miguel Lopez Alcaraz, Hjalmar Bouma, Nils Strodthoff:
MDS-ED: Multimodal Decision Support in the Emergency Department - a Benchmark Dataset for Diagnoses and Deterioration Prediction in Emergency Medicine. CoRR abs/2407.17856 (2024) - [i28]Juan Miguel Lopez Alcaraz, Nils Strodthoff:
CardioLab: Laboratory Values Estimation from Electrocardiogram Features - An Exploratory Study. CoRR abs/2407.18629 (2024) - [i27]Juan Miguel Lopez Alcaraz, Nils Strodthoff:
Estimation of Cardiac and Non-cardiac Diagnosis from Electrocardiogram Features. CoRR abs/2408.17329 (2024) - 2023
- [j13]Juan Miguel Lopez Alcaraz
Diffusion-based conditional ECG generation with structured state space models. Comput. Biol. Medicine 163: 107115 (2023) - [j12]Maximilian Springenberg
From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology. Medical Image Anal. 87: 102809 (2023) - [j11]Temesgen Mehari
Towards Quantitative Precision for ECG Analysis: Leveraging State Space Models, Self-Supervision and Patient Metadata. IEEE J. Biomed. Health Informatics 27(11): 5326-5334 (2023) - [j10]Juan Miguel Lopez Alcaraz, Nils Strodthoff:
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models. Trans. Mach. Learn. Res. 2023 (2023) - [j9]Johanna Vielhaben, Stefan Bluecher, Nils Strodthoff:
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees. Trans. Mach. Learn. Res. 2023 (2023) - [i26]Juan Miguel Lopez Alcaraz, Nils Strodthoff:
Diffusion-based Conditional ECG Generation with Structured State Space Models. CoRR abs/2301.08227 (2023) - [i25]Johanna Vielhaben, Stefan Blücher, Nils Strodthoff:
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees. CoRR abs/2301.11911 (2023) - [i24]Temesgen Mehari, Ashish Sundar, Alen Bosnjakovic, Peter M. Harris, Steven E. Williams, Axel Loewe, Olaf Dössel, Claudia Nagel, Nils Strodthoff, Philip J. Aston:
ECG Feature Importance Rankings: Cardiologists vs. Algorithms. CoRR abs/2304.02577 (2023) - [i23]Patrick Wagner, Temesgen Mehari, Wilhelm Haverkamp, Nils Strodthoff:
Explaining Deep Learning for ECG Analysis: Building Blocks for Auditing and Knowledge Discovery. CoRR abs/2305.17043 (2023) - [i22]Temesgen Mehari, Nils Strodthoff:
Towards quantitative precision for ECG analysis: Leveraging state space models, self-supervision and patient metadata. CoRR abs/2308.15291 (2023) - [i21]Markus Wenzel, Erik Grüner, Nils Strodthoff:
Insights Into the Inner Workings of Transformer Models for Protein Function Prediction. CoRR abs/2309.03631 (2023) - [i20]Tiezhi Wang, Nils Strodthoff:
S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models. CoRR abs/2310.06715 (2023) - [i19]Gabriel Ott, Yannik Schaubelt, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff:
Uncovering ECG Changes during Healthy Aging using Explainable AI. CoRR abs/2310.07463 (2023) - [i18]Nils Strodthoff, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp:
Cardiac and extracardiac discharge diagnosis prediction from emergency department ECGs using deep learning. CoRR abs/2312.11050 (2023) - 2022
- [j8]Stefan Blücher
PredDiff: Explanations and interactions from conditional expectations. Artif. Intell. 312: 103774 (2022) - [j7]Temesgen Mehari, Nils Strodthoff:
Self-supervised representation learning from 12-lead ECG data. Comput. Biol. Medicine 141: 105114 (2022) - [c3]Philip J. Aston, Temesgen Mehari, Alen Bosnjakovic, Peter M. Harris, Ashish Sundar, Steven E. Williams, Olaf Dössel, Axel Loewe
Multi-Class ECG Feature Importance Rankings: Cardiologists vs Algorithms. CinC 2022: 1-4 - [i17]Johanna Vielhaben, Stefan Blücher, Nils Strodthoff:
Sparse Subspace Clustering for Concept Discovery (SSCCD). CoRR abs/2203.06043 (2022) - [i16]Maximilian Springenberg, Annika Frommholz, Markus Wenzel, Eva Weicken, Jackie Ma, Nils Strodthoff:
From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in Histopathology. CoRR abs/2204.05044 (2022) - [i15]Juan Miguel Lopez Alcaraz, Nils Strodthoff:
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models. CoRR abs/2208.09399 (2022) - [i14]Temesgen Mehari, Nils Strodthoff:
Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models. CoRR abs/2211.07579 (2022) - 2021
- [j6]Nils Strodthoff
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. IEEE J. Biomed. Health Informatics 25(5): 1519-1528 (2021) - [j5]Nils Strodthoff
Inferring Respiratory and Circulatory Parameters from Electrical Impedance Tomography With Deep Recurrent Models. IEEE J. Biomed. Health Informatics 25(8): 3105-3111 (2021) - [i13]Stefan Blücher, Nils Strodthoff:
PredDiff: Explanations and Interactions from Conditional Expectations. CoRR abs/2102.13519 (2021) - [i12]Temesgen Mehari, Nils Strodthoff:
Self-supervised representation learning from 12-lead ECG data. CoRR abs/2103.12676 (2021) - [i11]Johanna Vielhaben, Markus Wenzel, Eva Weicken, Nils Strodthoff:
Predicting the Binding of SARS-CoV-2 Peptides to the Major Histocompatibility Complex with Recurrent Neural Networks. CoRR abs/2104.08237 (2021) - [i10]Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. CoRR abs/2106.13497 (2021) - 2020
- [j4]Nils Strodthoff
UDSMProt: universal deep sequence models for protein classification. Bioinform. 36(8): 2401-2409 (2020) - [j3]Johanna Vielhaben
USMPep: universal sequence models for major histocompatibility complex binding affinity prediction. BMC Bioinform. 21(1): 279 (2020) - [i9]Stefan Bluecher
Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning. CoRR abs/2003.01504 (2020) - [i8]Nils Strodthoff, Patrick Wagner, Tobias Schaeffter, Wojciech Samek:
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. CoRR abs/2004.13701 (2020) - [i7]Nils Strodthoff, Claas Strodthoff, Tobias Becher, Norbert Weiler, Inéz Frerichs:
Inferring respiratory and circulatory parameters from electrical impedance tomography with deep recurrent models. CoRR abs/2010.09622 (2020) - [i6]Johanna Vielhaben, Nils Strodthoff:
Generative Neural Samplers for the Quantum Heisenberg Chain. CoRR abs/2012.10264 (2020)
2010 – 2019
- 2019
- [j2]Nils Strodthoff
Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G. IEEE J. Sel. Areas Commun. 37(11): 2573-2587 (2019) - [c2]Jan Laermann, Wojciech Samek, Nils Strodthoff:
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training. GCPR 2019: 360-373 - [i5]Kim Nicoli
Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling. CoRR abs/1903.11048 (2019) - [i4]Jan Laermann, Wojciech Samek, Nils Strodthoff:
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training. CoRR abs/1906.00735 (2019) - [i3]Kim A. Nicoli
Asymptotically Unbiased Generative Neural Sampling. CoRR abs/1910.13496 (2019) - 2018
- [c1]Nils Strodthoff, Baris Göktepe
Machine Learning for Early HARQ Feedback Prediction in 5G. GLOBECOM Workshops 2018: 1-6 - [i2]Nils Strodthoff, Claas Strodthoff:
Detecting and interpreting myocardial infarctions using fully convolutional neural networks. CoRR abs/1806.07385 (2018) - [i1]Nils Strodthoff, Baris Göktepe, Thomas Schierl, Cornelius Hellge, Wojciech Samek:
Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G. CoRR abs/1807.10495 (2018) - 2017
- [j1]Anton K. Cyrol
FormTracer. A mathematica tracing package using FORM. Comput. Phys. Commun. 219: 346-352 (2017)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-10 20:46 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: