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ndonnx
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public |
ONNX backed array library compliant with Array API standard.
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2026-03-23 |
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lbapcommon
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public |
Common utilities used by LHCb DPA WP2 related software
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2026-03-23 |
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helios
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public |
Heidelberg LiDAR Operations Simulator ++
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2026-03-23 |
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symbolic
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public |
A python library for dealing with symbol files and more.
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2026-03-23 |
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conda-sphinx-theme
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public |
Conda theme for Sphinx
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2026-03-23 |
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geoai
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public |
A Python package for integrating Artificial Intelligence with geospatial data analysis and visualization
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2026-03-23 |
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geoai-py
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public |
A Python package for integrating Artificial Intelligence with geospatial data analysis and visualization
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2026-03-23 |
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r-mlr3tuning
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public |
Implements methods for hyperparameter tuning with 'mlr3', e.g. Grid Search, Random Search, or Simulated Annealing. Various termination criteria can be set and combined. The class 'AutoTuner' provides a convenient way to perform nested resampling in combination with 'mlr3'.
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2026-03-23 |
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dsconfig
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public |
Library and utilities for Tango device configuration.
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2026-03-23 |
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optlang
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public |
optlang - sympy based mathematical programming language
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2026-03-23 |
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xarray-prism
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public |
A multi-format and multi-storage xarray engine with automatic engine detection.
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2026-03-23 |
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r-huge
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public |
Provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline. In preprocessing stage, the nonparanormal(npn) transformation is applied to help relax the normality assumption. In the graph estimation stage, the graph structure is estimated by Meinshausen-Buhlmann graph estimation or the graphical lasso, and both methods can be further accelerated by the lossy screening rule preselecting the neighborhood of each variable by correlation thresholding. We target on high-dimensional data analysis usually d >> n, and the computation is memory-optimized using the sparse matrix output. We also provide a computationally efficient approach, correlation thresholding graph estimation. Three regularization/thresholding parameter selection methods are included in this package: (1)stability approach for regularization selection (2) rotation information criterion (3) extended Bayesian information criterion which is only available for the graphical lasso.
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2026-03-23 |
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streamlit-folium
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public |
Render Folium objects in Streamlit
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2026-03-23 |
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arviz-bokeh
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public |
Exploratory analysis of Bayesian models with Python
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2026-03-23 |
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arviz
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public |
Exploratory analysis of Bayesian models with Python
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2026-03-23 |
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arviz-plotly
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public |
Exploratory analysis of Bayesian models with Python
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2026-03-23 |
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pymc-base
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public |
Probabilistic Programming in Python
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2026-03-23 |
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pymc
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public |
Probabilistic Programming in Python
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2026-03-23 |
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gtk4
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public |
Version 4 of the Gtk+ graphical toolkit
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2026-03-23 |
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eodag
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public |
Earth Observation Data Access Gateway
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2026-03-23 |
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miniaudio
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public |
python bindings for the miniaudio library and its decoders (mp3, flac, ogg vorbis, wav)
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2026-03-23 |
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r-mwcsr
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public |
Algorithms for solving various Maximum Weight Connected Subgraph Problems, including variants with budget constraints, cardinality constraints, weighted edges and signals. The package represents an R interface to high-efficient solvers based on relax-and-cut approach (Álvarez-Miranda E., Sinnl M. (2017) <doi:10.1016/j.cor.2017.05.015>) mixed-integer programming (Loboda A., Artyomov M., and Sergushichev A. (2016) <doi:10.1007/978-3-319-43681-4_17>) and simulated annealing.
|
2026-03-23 |
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azure-synapse-artifacts
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public |
Microsoft Azure Synapse Artifacts Client Library for Python
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2026-03-23 |
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google-cloud-storage
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public |
Python Client for Google Cloud Storage
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2026-03-23 |
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rpy2
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public |
Python interface to the R language (embedded R)
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2026-03-23 |
