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Computer Simulation

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PathMLP: Smooth path towards high-order homophily.

Neural networks : the official journal of the International Neural Network Society
Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph neural networks (GNNs) and impeding their performance. Intriguingly, fr...

The Artificial Neural Twin - Process optimization and continual learning in distributed process chains.

Neural networks : the official journal of the International Neural Network Society
Industrial process optimization and control is crucial to increase economic and ecologic efficiency. However, data sovereignty, differing goals, or the required expert knowledge for implementation impede holistic implementation. Further, the increasi...

Asynchronous Numerical Spiking Neural Membrane Systems with Local Synchronization.

International journal of neural systems
Since the spiking neural P system (SN P system) was proposed in 2006, it has become a research hotspot in the field of membrane computing. The SN P system performs computations through the encoding, processing, and transmission of spiking information...

Deep reinforcement learning control of combined chemotherapy and anti-angiogenic drug delivery for cancerous tumor treatment.

Computers in biology and medicine
By virtue of the chronic and dangerous nature of cancer, researchers have explored various approaches to managing the abnormal cell growth associated with this disease using novel treatment methods. This study introduces a control system based on nor...

Depth estimation from monocular endoscopy using simulation and image transfer approach.

Computers in biology and medicine
Obtaining accurate distance or depth information in endoscopy is crucial for the effective utilization of navigation systems. However, due to space constraints, incorporating depth cameras into endoscopic systems is often impractical. Our goal is to ...

Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning.

Scientific reports
Transcranial magnetic stimulation (TMS) has emerged as a promising neuromodulation technique with both therapeutic and diagnostic applications. As accurate coil placement is known to be essential for focal stimulation, computational models have been ...

Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.

Magma (New York, N.Y.)
We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and...

Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors.

Journal of computer-aided molecular design
The development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thomas et al. Clinical Development Success Rates and Contributing Factors 2011-2020, 2021). To increase the probability of success a...

Interplay between depth and width for interpolation in neural ODEs.

Neural networks : the official journal of the International Neural Network Society
Neural ordinary differential equations have emerged as a natural tool for supervised learning from a control perspective, yet a complete understanding of the role played by their architecture remains elusive. In this work, we examine the interplay be...

Reduced order modelling of intracranial aneurysm flow using proper orthogonal decomposition and neural networks.

International journal for numerical methods in biomedical engineering
Reduced order modelling (ROMs) methods, such as proper orthogonal decomposition (POD), systematically reduce the dimensionality of high-fidelity computational models and potentially achieve large gains in execution speed. Machine learning (ML) using ...