Abstract: This study introduces a novel approach that combines a variational autoencoder and Bayesian optimization to accelerate the simultaneous parameter and topology optimization of interior ...

Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahçeşehir University, Istanbul 34349, Turkey Lab for Innovative Drugs (Lab4IND), ...

├── data_pre/ # Data preprocessing modules │ ├── data_pre.py # Data preprocessing script │ └── dataset.py # Dataset class definition ├── dataset/ # Data directory │ ├── SRU_data.npy # Process data in ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...

Anomaly detection is a typical binary classification problem under the condition of unbalanced samples, which has been widely used in various fields of data mining. For example, it can help detect ...

ABSTRACT: In this paper, we are concerned with the following nonlocal Schrödinger equations − ℒ K u+V( x )u=f( x,u ), x∈ ℝ N , where − ℒ K is an integro-differential operator of fractional Laplacian ...

Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...

We introduce a self-guided, interactive JupyterLab to familiarize undergraduate students with introductory quantum mechanics concepts. In the lab, the linear variational method is applied to a ...

Deep learning methods for generating artificial data in health care include data augmentation by variational autoencoders (VAE) technology. Objective: We aimed to test the feasibility of generating ...

Introduction: Electromagnetic brain imaging is the reconstruction of brain activity from non-invasive recordings of electroencephalography (EEG), magnetoencephalography (MEG), and also from invasive ...