Treffer 1 - 20 von 3.223

1

Two approaches to survival analysis of open source Python projects
Robinson, Derek ; Enns, Keanelek ; Koulecar, Neha ; et al.
Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension. :660-669

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2

BSTPP: a python package for Bayesian spatiotemporal point processes.
Manring, Isaac ; Wang, Honglang ; Mohler, George ; et al.
Journal of Applied Statistics. Oct2025, Vol. 52 Issue 13, p2524-2543. 20p.

Bayesian analysis Spatiotemporal processes Point processes Python programming langu... Inference (Logic) Latent variables
Fachzeitschrift
6

Bayesian statistical modeling with Stan, R, and Python
Matsuura, Kentaro, VerfasserIn, aut ; Matsuura, Kentaro, VerfasserIn, aut
2022

Buch
7

Analysis of Chinese Comments on Douban Based on Naive Bayes
Xue, Jingjing ; Liu, Kun ; Lu, Zeshan ; et al.
Proceedings of the 2nd International Conference on Big Data Technologies. :121-124

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8

pgmpy: A Python Toolkit for Bayesian Networks.
Ankan, Ankur ; Textor, Johannes
Journal of Machine Learning Research. Jan-Dec2024, Vol. 25, p1-8. 8p.

Bayesian analysis Decision making Causal inference Machine learning Source code
Fachzeitschrift
10

pyBNBowTie: Python library for Bow-Tie Analysis based on Bayesian Networks.
Zurheide, Frank T. ; Hermann, Eckehard ; Lampesberger, Harald
Procedia Computer Science. 2021, Vol. 180, p344-351. 8p.

Bayesian analysis Python programming langu... Computer software Risk assessment
Fachzeitschrift
11

Improving ADM1 predictions via Bayesian analysis for continuous anaerobic digestion
Liu, Yanxin ; Jiang, Ying ; Nasar, Nasreen ; et al.
In Journal of Environmental Management 15 January 2026 398

Fachzeitschrift
12

Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series.
Thomas, Andrew M. ; Jauch, Michael ; Matteson, David S.
Technometrics. Nov2025, Vol. 67 Issue 4, p693-705. 13p.

Multivariate analysis Bayesian analysis Change-point problems Logistic regression anal... Topology Data transformations (St...
Fachzeitschrift
13

A different approach for causal impact analysis on Python with Bayesian structural time-series and bidirectional LSTM models
Fotia, Pasquale ; Ferrara, Massimiliano
Atti della Accademia Peloritana dei Pericolanti : Classe di Scienze Fisiche, Matematiche e Naturali, Vol 101, Iss 2, p A12 (2023)
Atti della Accademia Peloritana dei Pericolanti-Classe di Scienze Fisiche, Matematiche e Naturali; Vol 101, No 2 (2023); A12
Atti della Accademia Peloritana dei Pericolanti. Classe di Scienze Fisiche, Matematiche e Naturali; Vol 101, No 2 (2023); A12

Mathematics Computer Science Q1-390 Science (General) Causal impact analysis Bi-LSTM, Deep Learning
Fachzeitschrift
14

Bayesian analysis suggests independent development of sensitization to different fungal allergens
Rodinkova, Victoria ; Yuriev, Serhii ; Mokin, Vitalii ; et al.
In World Allergy Organization Journal May 2024 17(5)

Fachzeitschrift
15

ArviZ a unified library for exploratory analysis of Bayesian models in Python.
Ravin Kumar ; Colin Carroll ; Ari Hartikainen ; et al.
J. Open Source Softw.. 4(33):1143-1143

Fachzeitschrift
16

Bayesian Survey Analysis: Multilevel Extension
Paczkowski, Walter R. ; Paczkowski, Walter R.
Modern Survey Analysis : Using Python for Deeper Insights. :303-335

E-Book
17

Bayesian Survey Analysis: Introduction
Paczkowski, Walter R. ; Paczkowski, Walter R.
Modern Survey Analysis : Using Python for Deeper Insights. :251-302

E-Book
18

Bayesian Modeling and Computation in Python Learning.
Lazic, Stanley E.
Journal of the Royal Statistical Society: Series A (Statistics in Society). Dec2022 Supplement 2, Vol. 185, pS764-S765. 2p.

Programming languages Bayesian analysis Time series analysis Computer science Python programming langu...
Fachzeitschrift
19

Bayesian Analysis with Python Ed. 2
Martin, Osvaldo ; Martin, Osvaldo ; Martin, Osvaldo ; et al.

E-Ressource
20

A Comparative Analysis of Hyperopt as Against Other Approaches for Hyper-Parameter Optimization of XGBoost
Putatunda, Sayan ; Rama, Kiran
Proceedings of the 2018 International Conference on Signal Processing and Machine Learning. :6-10

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