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PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series with missing values.
Bayesian Temporal Factorization for Multidimensional Time Series Prediction
Xinyu Chen and Lijun Sun · 1910
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Continuous representations of time-series gene expression data
Ziv Bar-Joseph, Georg K Gerber, David K Gifford, Tommi S Jaakkola, and Itamar Simon · 2003
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F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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API design for machine learning software: experiences from the scikit-learn project
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H5py/h5py: 2.7.0, March 2017
Andrew Collette, James Tocknell, Thomas A Caswell, Darren Dale, Ulrik Kofoed Pedersen, Aleksandar Jelenak, Andrea Bedini, Martin Raspaud, Jialin Lei, Laurence Hole, Matthieu Brucher, Martin Teichmann, Ghislain Antony Vaillant, Jakirkham, Konrad Hinsen, Pierre De Buyl, Axel Huebl, Florian Rathgeber, Toon Verstraelen, Spaghetti Sort, Simon Gregor Ebner, Smutch, Matthew Zwier, Antony Lee, Matthew Brett, Joseph Kleinhenz, Jonah Bernhard, John Tyree, Antoine Pitrou, and Andy Salnikov · 2017
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imputeTS: Time Series Missing Value Imputation in R
Steffen Moritz and Thomas Bartz-Beielstein · 2017
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Hyperparameter optimization
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
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Array programming with NumPy
Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Río, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke, and Travis E. Oliphant · 2020
Forecasting loss of signal in optical networks with machine learning
Wenjie Du, David Cote, Chris Barber, and Yan Liu · 2021
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NNI: Neural Network Intelligence, 1 2021
Microsoft · 2021
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Autoimpute
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Tsi-bench: Benchmarking time series imputation
Wenjie Du, Jun Wang, Linglong Qian, Yiyuan Yang, Zina Ibrahim, Fanxing Liu, Zepu Wang, Haoxin Liu, Zhiyuan Zhao, Yingjie Zhou, et al · 2024
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Imputegap: A comprehensive library for time series imputation
Quentin Nater, Mourad Khayati, and Jacques Pasquier · 2025
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Deep learning for multivariate time series imputation: A survey
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Mind the gap: an experimental evaluation of imputation of missing values techniques in time series
Mourad Khayati, Alberto Lerner, Zakhar Tymchenko, and Philippe Cudré-Mauroux · 2020
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SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python
Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, C J Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R. Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, and SciPy 1.0 Contributors · 2020
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Jun Wang, Wenjie Du, Yiyuan Yang, Linglong Qian, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, and Qingsong Wen · 2025
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