Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Deep neural networks have rapidly advanced, with many models demonstrating outstanding performance. However, robustness is crucial for ensuring the safety and stability of artificial intelligence, ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP)─the problem of identifying the stable crystal structures that will form from a given molecule based ...

Studies have shown that deep neural networks (DNNs) are susceptible to adversarial attacks, which can cause misclassification. The adversarial attack problem can be regarded as an optimization problem ...

machine-learning automation genetic-programming hyperparameter-optimization evolutionary-algorithms multimodality automl automated-machine-learning parameter-tuning structural-learning fedot Updated 2 ...