prof. dr. Dirk Deschrijver
- ORCID iD
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0000-0001-6600-1792
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- Journal Article
- A2
- open access
The role of trustworthy and reliable AI for multiple sclerosis
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- Journal Article
- A1
- open access
Deep learning-based event counting for apnea-hypopnea index estimation using recursive spiking neural networks
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Interpretable machine learning models for COPD ease of breathing estimation
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- Conference Paper
- C1
- open access
Improving features for multiple sclerosis disability progression prediction through temporal alignment of hospital visits
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- Conference Paper
- P1
- open access
Modeling microwave S-parameters using frequency-scaled rational Gaussian process kernels
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- Journal Article
- A2
- open access
Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study
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- Journal Article
- A1
- open access
ECGencode : compact and computationally efficient deep learning feature encoder for ECG signals
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- Journal Article
- A1
- open access
Unsupervised transfer learning across different data modalities for bearing's speed identification
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- Conference Paper
- C1
- open access
Modeling and co-simulation framework for multi-wavelength photonic integrated circuits : a wideband complex vector fitting approach
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- Journal Article
- A2
- open access
On the role of Bayesian learning for electronic design automation : a survey