Applications of machine learning for studying local solvation environments

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The field of text-to-video retrieval has advanced significantly with the evolution of language models and large-scale pre-training on generated caption-video pairs. Current methods predominantly focus on visual and event-based details, making retrieval lar ...

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

This dataset contains some images (TIFF image data) of brain juvenile rats Wistar Han (P14) scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pi ...

Utilization of small molecules as passivation materials for perovskite solar cells (PSCs) has gained significant attention recently, with hundreds of small molecules demonstrating passivation effects. In this study, a high-accuracy machine learning model i ...

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Raw data and Python code for the manuscript "Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution". All data files and source code are provided in a zip file. .ipynb file is a python jupyter notebook file whi ...

Small scale ultrasonic piezoelectric actuators performance strongly depends on not well-known contact dynamics. Deep Neural Network (DNN) sees their use in physic simulation growing as their flexibility allows better performance especially when dynamics la ...

Deep learning algorithms demonstrate a surprising ability to learn high-dimensional tasks from limited examples. This is commonly attributed to the depth of neural networks, enabling them to build a hierarchy of abstract, low-dimensional data representatio ...

The Industrial Internet of Things (IIoT) is reshaping manufacturing, industrial processes, and infrastructure management. By fostering new levels of automation, efficiency, and predictive maintenance, IIoT is transforming traditional industries into intell ...

Applications of machine learning for studying local solvation environments

Chattez avec Graph Search

Beyond Essentials: Nuanced and Diverse Text-to-video Retrieval

Surface segregation in high-entropy alloys from alchemical machine learning

Nissl_4, Raw images for Machine learning for histological annotation and quantification of cortical layers

Machine Learning for Screening Small Molecules as Passivation Materials for Enhanced Perovskite Solar Cells

Live-cell imaging powered by computation

Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution

Normal Contact Force Estimation Using Deep Learning

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model

Physics-Enhanced Graph Neural Networks for Soft Sensing in Industrial Internet of Things