Nils Strodthoff | DeepAI

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∙ 09/07/2023

Insights Into the Inner Workings of Transformer Models for Protein Function Prediction

Motivation: We explored how explainable AI (XAI) can help to shed light ...

0 Markus Wenzel, et al. ∙

∙ 08/29/2023

Towards quantitative precision for ECG analysis: Leveraging state space models, self-supervision and patient metadata

Deep learning has emerged as the preferred modeling approach for automat...

0 Temesgen Mehari, et al. ∙

∙ 05/26/2023

Explaining Deep Learning for ECG Analysis: Building Blocks for Auditing and Knowledge Discovery

Deep neural networks have become increasingly popular for analyzing ECG ...

0 Patrick Wagner, et al. ∙

∙ 04/05/2023

ECG Feature Importance Rankings: Cardiologists vs. Algorithms

Feature importance methods promise to provide a ranking of features acco...

0 Temesgen Mehari, et al. ∙

∙ 01/27/2023

Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees

The completeness axiom renders the explanation of a post-hoc XAI method ...

0 Johanna Vielhaben, et al. ∙

∙ 01/19/2023

Diffusion-based Conditional ECG Generation with Structured State Space Models

Synthetic data generation is a promising solution to address privacy iss...

0 Juan Miguel Lopez Alcaraz, et al. ∙

∙ 11/14/2022

Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models

The field of deep-learning-based ECG analysis has been largely dominated...

0 Temesgen Mehari, et al. ∙

∙ 08/19/2022

Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models

The imputation of missing values represents a significant obstacle for m...

1 Juan Miguel Lopez Alcaraz, et al. ∙

∙ 03/11/2022

Sparse Subspace Clustering for Concept Discovery (SSCCD)

Concepts are key building blocks of higher level human understanding. Ex...

0 Johanna Vielhaben, et al. ∙

∙ 06/25/2021

On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy

There is an increasing number of medical use-cases where classification ...

10 Vignesh Srinivasan, et al. ∙

∙ 04/16/2021

Predicting the Binding of SARS-CoV-2 Peptides to the Major Histocompatibility Complex with Recurrent Neural Networks

Predicting the binding of viral peptides to the major histocompatibility...

0 Johanna Vielhaben, et al. ∙

∙ 03/23/2021

Self-supervised representation learning from 12-lead ECG data

We put forward a comprehensive assessment of self-supervised representat...

0 Temesgen Mehari, et al. ∙

∙ 02/26/2021

PredDiff: Explanations and Interactions from Conditional Expectations

PredDiff is a model-agnostic, local attribution method that is firmly ro...

0 Stefan Blücher, et al. ∙

∙ 12/18/2020

Generative Neural Samplers for the Quantum Heisenberg Chain

Generative neural samplers offer a complementary approach to Monte Carlo...

0 Johanna Vielhaben, et al. ∙

∙ 10/19/2020

Inferring respiratory and circulatory parameters from electrical impedance tomography with deep recurrent models

Electrical impedance tomography (EIT) is a noninvasive imaging modality ...

0 Nils Strodthoff, et al. ∙

∙ 04/28/2020

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

Electrocardiography is a very common, non-invasive diagnostic procedure ...

16 Nils Strodthoff, et al. ∙

∙ 03/03/2020

Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning

Machine learning has the potential to aid our understanding of phase str...

0 Stefan Bluecher, et al. ∙

∙ 10/29/2019

Asymptotically Unbiased Generative Neural Sampling

We propose a general framework for the estimation of observables with ge...

0 Kim A. Nicoli, et al. ∙

∙ 06/03/2019

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training

We study the recently introduced stability training as a general-purpose...

0 Jan Laermann, et al. ∙

∙ 03/26/2019

Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling

In this comment on "Solving Statistical Mechanics Using Variational Auto...

2 Kim Nicoli, et al. ∙

∙ 07/27/2018

Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G

We investigate Early Hybrid Automatic Repeat reQuest (E-HARQ) feedback s...

0 Nils Strodthoff, et al. ∙

∙ 06/18/2018

Detecting and interpreting myocardial infarctions using fully convolutional neural networks

We consider the detection of myocardial infarction in electrocardiograph...

0 Nils Strodthoff, et al. ∙

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