Resistance training (RT), typically performed over several weeks to months, has consistently been shown to elicit small-to-moderate increases in skeletal muscle mass (Steele et al., 2023). Recently, ...

As a well-known Bayesian network structure learning algorithm in equivalence class space (E-space), Greedy equivalence search (GES) is used in many fields. However, it encounters high complexity when ...

BRO (Behavior-Regularized Offline RL): Regularize offline RL policies by constraining them to stay close to the behavior policy in the dataset, mitigating distributional shift. Enhanced performance in ...

Limited research in Saudi Arabia has devolved into the prevalence and genetic diversity of begomoviruses. Utilizing Illumina MiSeq sequencing, we obtained 21 full-length begomovirus sequences (2.7–2.8 ...

Abstract: Contrastive unsupervised representation learning (CURL) is a technique that seeks to learn feature sets from unlabeled data. It has found widespread and successful application in ...

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional ...

A modern, PyTorch-based library for Bayesian changepoint detection in time series data. This library implements both online and offline methods with GPU acceleration support for high-performance ...

Jitterbug 2.0 is a modern, completely rewritten Python framework for detecting network congestion through jitter analysis and change point detection in Round-Trip Time (RTT) measurements. This ...

Copyright © Not subject to U.S. Copyright. Published 2005 American Chemical Society You may have access to this article through your institution. Your institution ...