Abstract: Computing derivatives of noisy measurement data is ubiquitous in the physical, engineering, and biological sciences, and it is often a critical step in developing dynamic models or designing ...
Recommend Python 3.12 or above PyTorch 2.4 or above While PtyRAD can run on CPU, GPU is strongly suggested for high-speed ptychographic reconstructions. First, create and activate a new conda ...
Abstract: Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inherent part ...
We thank Petr Sulc, Tom Ouldridge, Jonathan Doye, Lorenzo Rovigatti, Erik Poppleton, and Ard Louis for support and helpful discussions surrounding the oxDNA force field and the oxDNA ecosystem. We ...
derivative is a Python package for differentiating noisy data. The package showcases a variety of improvements that can be made over finite differences when data is not clean. Kaptanoglu et al., (2022 ...
Balyasny Asset Management is teaching its pipeline of up-and-coming analysts how to code in hopes it'll give the $20 billion firm an edge. "The analyst of tomorrow is not going to be an analyst that ...
ABSTRACT: Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential ...
Glucose (Gluc) and glutamine (Gln) are thought to be essential for cell growth, acting as a main source of carbon and energy for various mammalian cell types (Vriezen et al., 1997; Vergara et al., ...
As we learn, dynamic memory processes build structured knowledge across our experiences. Such knowledge enables the formation of internal models of the world that we use to plan, make decisions, and ...
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