214.423 hasil untuk machine learning
Menampilkan 221–240 · 0,82 detik · RSS
-
Artikel Jurnal Teks lengkap
Machine Learning Characterization of COPD Subtypes
…example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the…
-
Artikel Jurnal Teks lengkap
Machine learning in genetics and genomics
The field of machine learning promises to enable computers to assist humans in making sense of large, complex data sets. In this review, we outline some of the main applications of machine learning to genetic and genomic data. In the process, we identify some recurrent challenges associated with…
-
Artikel Jurnal Teks lengkap
Overview of Machine Learning Process Modelling
Much research has been conducted in the area of machine learning algorithms; however, the question of a general description of an artificial learner’s (empirical) performance has mainly remained unanswered. A general, restrictions-free theory on its performance has not been developed yet. In this…
-
Artikel Jurnal Teks lengkap
Machine Learning for Light Sensor Calibration
Sunlight incident on the Earth’s atmosphere is essential for life, and it is the driving force of a host of photo-chemical and environmental processes, such as the radiative heating of the atmosphere. We report the description and application of a physical methodology relative to how an ensemble of…
-
Artikel Jurnal Teks lengkap
Quasar: Easy Machine Learning for Biospectroscopy
…to follow quickly changing, cutting-edge research demands. Finally, as machine learning techniques penetrate data analysis pipelines of the natural sciences, we see the growing demand for user-friendly and flexible tools to fuse machine learning with spectroscopy datasets. In our opinion…
-
Artikel Jurnal Teks lengkap
Multiscale Enhanced Sampling Using Machine Learning
…the CG model with the dynamics on the reduced subspace generated by a machine learning approach, the variational autoencoder (VAE). The molecular dynamic (MD) trajectories of the ribose-binding protein (RBP) in both the closed and open forms were used as the input by extracting the inter-residue…
-
Artikel Jurnal Teks lengkap
Universal activation function for machine learning
This article proposes a universal activation function (UAF) that achieves near optimal performance in quantification, classification, and reinforcement learning (RL) problems. For any given problem, the gradient descent algorithms are able to evolve the UAF to a suitable activation function by…
-
Artikel Jurnal Teks lengkap
Machine learning and applications in microbiology
…data patterns without an artificial intelligence application called machine learning. Applying machine learning to address biological problems is expected to grow at an unprecedented rate, yet it is perceived by the uninitiated as a mysterious and daunting entity entrusted to the domain of…
-
Artikel Jurnal Teks lengkap
Machine Learning Applications in Drug Repurposing
…and diseases, the tremendous growth of publicly available large-scale machine learning methods supplies the state-of-the-art application of data science to signaling disease, medicine, therapeutics, and identifying targets with the least error. In this article, we introduce guidelines on strategies…
-
Artikel Jurnal Teks lengkap
R.ROSETTA: an interpretable machine learning framework
BACKGROUND: Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what…
-
Artikel Jurnal Teks lengkap
Beyond sequence: Structure-based machine learning
…protein structure information is as prevalent and ubiquitous as sequence. Machine learning in protein bioinformatics has been dominated by sequence-based methods, but this is now changing to make use of the deluge of rich structural information as input. Machine learning methods making use of…
-
Artikel Jurnal Teks lengkap
Quantum machine learning beyond kernel methods
Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and studied extensively. Yet, our understanding of how these models…
-
Artikel Jurnal Teks lengkap
Leveraging theory for enhanced machine learning
The application of machine learning to the materials domain has traditionally struggled with two major challenges: a lack of large, curated datasets and the need to understand the physics behind the machine learning prediction. The former problem is particularly acute in the polymers domain. Here…
-
Artikel Jurnal Teks lengkap
Monochromatic image reconstruction via machine learning
…images, suffering from beam-hardening effects. In this paper, a machine learning-based approach is proposed to correct the model mismatch to achieve quantitative CT imaging. Specifically, a one-dimensional network model is proposed to learn a non-linear transform from a training dataset to map a…
-
Artikel Jurnal Teks lengkap
QDataSet, quantum datasets for machine learning
The availability of large-scale datasets on which to train, benchmark and test algorithms has been central to the rapid development of machine learning as a discipline. Despite considerable advancements, the field of quantum machine learning has thus far lacked a set of comprehensive large-scale…
-
Artikel Jurnal Teks lengkap
Machine learning partners in criminal networks
…networks remains little explored. Here, by combining graph representation learning and machine learning methods, we show that structural properties of political corruption, police intelligence, and money laundering networks can be used to recover missing criminal partnerships, distinguish among…
-
Artikel Jurnal Teks lengkap
Protein Function Analysis through Machine Learning
Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein…
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.