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Statistical analysis of vegetable productivity dynamics of Uzbekistan [PDF]
BIO Web of Conferences, 2023 In all fields, there are a lot of random events at a given time. In particular, the process of growing agricultural crops, which is repeated over a certain period, that is, seasonally, is the basis for our analysis as a discrete {Yt,t ∈ T} random dynamic
Fayziev Akhtamjon +3 more
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Technometrics, 2021 A machine learning system, in general, learns from the environment, but statistical machine learning programs (systems) learn from the data. This chapter presents techniques for statistical machine learning using Support Vector Machines (SVM) to ...
Yuhai Wu
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Manual for Theoretical Chemistry, 2021 Professor Chen Ning Yang has made seminal and influential contributions in many different areas in theoretical physics. This talk focuses on his contributions in statistical mechanics, a field in which Professor Yang has held a continual interest for ...
Uwe-Jens Wiese, Albert Einstein
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Frontiers in Psychiatry, 2022 BackgroundIdentifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited.
Dong Yun Lee +9 more
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Seaborn: Statistical Data Visualization
Journal of Open Source Software, 2021 seaborn is a library for making statistical graphics in Python. It provides a high-level interface to matplotlib and integrates closely with pandas data structures. Functions in the seaborn library expose a declarative, dataset-oriented API that makes it
Michael L. Waskom
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Clustering CITE-seq data with a canonical correlation-based deep learning method
Frontiers in Genetics, 2022 Single-cell multiomics sequencing techniques have rapidly developed in the past few years. Among these techniques, single-cell cellular indexing of transcriptomes and epitopes (CITE-seq) allows simultaneous quantification of gene expression and surface ...
Musu Yuan +4 more
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Probabilistic deconvolution of PET images using informed priors
Frontiers in Nuclear Medicine, 2023 PurposeWe present a probabilistic approach to medical image analysis that requires, and makes use of, explicit prior information provided by a medical expert.
Thomas Mejer Hansen +9 more
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An introduction to statistical learning with applications in R
Statistical Theory and Related Fields, 2021 The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Fariha Sohil +2 more
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2014 In this paper, we propose a novel neural network model called RNN Encoder‐ Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixedlength vector representation, and the other decodes the ...
Kyunghyun Cho +6 more
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performance: An R Package for Assessment, Comparison and Testing of Statistical Models
Journal of Open Source Software, 2021 A crucial part of statistical analysis is evaluating a model's quality and fit, or performance. During analysis, especially with regression models, investigating the fit of models to data also often involves selecting the best fitting model amongst many ...
D. Lüdecke +4 more
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