This package provides a set of tools to perform various simulations bringing together machine-learning methods with quantum simulations of atomic systems. Here are some features implemented in the ...

To address this challenge, this project aims to develop a machine learning model to identify duplicate question pairs, enhancing the overall user experience by providing canonical questions with ...

Introduction: Recent advances in machine learning provide new possibilities to process and analyse observational patient data to predict patient outcomes. In this paper, we introduce a data processing ...

These approaches have been used to discover new orthogonal pairs for efficient non-canonical amino acid incorporation. HORNET, a method that uses unsupervised machine learning and deep neural ...

Sensor-based imaging data serves as a rich source of information for machine learning ... making process of the deep learning model. The practical application involves taking an input image that the ...

covering about 100,000 CpG sites and is based on a reference-free analysis pipeline. Results: Resulting machine learning-based classifiers showed powerful correct classification rates discriminating ...

One critical action President Biden can take right now is to permanently shut down the Dakota Access Pipeline (DAPL). The pipeline is currently operating illegally, even as the ongoing legal battles ...

Many techniques in computational materials science require scientists to identify the right set of parameters that capture ...

Machine learning (ML) transforms the design of heterogeneous catalysts, traditionally driven by trial and error due to the ...

Given the vast scope of this issue, it's surprising that we have a limited understanding of what preserves and enhances ...

With volatility so closely tied to investment risk and returns, it's no wonder that a statistical method that captured ...