Reverse Dependencies of sphinxcontrib-bibtex
The following projects have a declared dependency on sphinxcontrib-bibtex:
- hsnf — Computing Hermite normal form and Smith normal form.
- imbalanced-ensemble — Toolbox for ensemble learning on class-imbalanced dataset.
- imbalanced-learn — Toolbox for imbalanced dataset in machine learning
- inequality — inequality: Spatial inequality analysis
- infercnvpy — Infercnv is a scalable python library to infer copy number variation (CNV) events from single cell transcriptomics data. It is heavliy inspired by InferCNV, but plays nicely with scanpy and is much more scalable.
- interface-region-imaging-spectrograph — A Python library for analyzing solar observations from the Interface Region Imaging Spectrograph (IRIS).
- invert4geom — Constrained gravity inversion to recover the geometry of a density contrast.
- iop4 — A rewrite of IOP3, a pipeline to work with photometry and polarimetry of optical data from CAHA and OSN.
- ipypublish — A workflow for creating and editing publication ready scientific reports, from one or more Jupyter Notebooks
- iterative-ensemble-smoother — A library for the iterative ensemble smoother algorithm.
- Jupinx — Jupinx extension: Convert your RST files into into different formats like notebook, pdf, html.
- jupyter_book — Build a book with Jupyter Notebooks and Sphinx.
- jupyter-federation — Jupyter Federation
- jupyterbook-latex — Latex specific features for jupyter book
- karr-lab-aws-manager — Package to manage aws services run by karr lab
- kikuchipy — Processing, simulating, and indexing of electron backscatter diffraction (EBSD) patterns
- kooplearn — A package to learn Koopman operators
- korner — korner
- kornia — Open Source Differentiable Computer Vision Library for PyTorch
- krotov — Python implementation of Krotov's method for quantum optimal control
- kuehn-et-al-fdm — Implementations of the Kuehn et al. 2024 Fault Displacement Model
- lapy — A package for differential geometry on meshes (Laplace, FEM)
- lbmpy — Code Generation for Lattice Boltzmann Methods
- lds-python — Linear Dynamical Systems
- lenskit — The LensKit toolkit for recommender systems research.
- lenskit-implicit — LensKit wrappers for the Implicit package.
- libNeuroML — A Python library for working with NeuroML descriptions of neuronal models
- libpypsg — A Python library for accessing the Planetary System Generator.
- libpysal — Core components of PySAL - A library of spatial analysis functions
- lightkde — Lightning fast, lightweight, and reliable kernel density estimation.
- litebird-sim — Simulation tools for the LiteBIRD experiment
- lkauto — LensKit-Auto is built as a wrapper around the Python LensKit recommender-system library. It automates algorithm selection and hyper parameter optimization an can build ensemble models based on the LensKit models.
- llg3d — Solveur pour l'équation de Landau-Lifshitz-Gilbert stochastique en 3D
- llm-check — A series of coherence and calibration checks for LLMs.
- lstcam-calib — Camera calibration code for the LSTCam
- lumflux — Illuminating web applications.
- macro-lightning — Constraining Macro Dark Matter Models with Lightning.
- madflow — Package for GPU fixed order calculations
- madjax — differentiable matrix elements
- mag-net — Magnetic Core Loss Modeling using ML
- mapca — Moving Average Principal Component Analysis for fMRI data
- mapclassify — Classification Schemes for Choropleth Maps.
- maples-dr — Utilities python library for the public dataset of retinal structures: MAPLES-DR.
- masspy — MASSpy is a package for dynamic modeling of biological processes.
- matcouply — Regularized coupled matrix factorisation with AO-ADMM
- MBIRJAX — High-performance tomographic reconstruction
- MDAnalysis — An object-oriented toolkit to analyze molecular dynamics trajectories.
- meddlr — Meddlr is a config-driven framework built to simplify ML-based medical image reconstruction and analysis.
- meegsim — Building blocks (waveforms, SNR, connectivity) for M/EEG simulations with MNE-Python
- menelaus — This library implements algorithms for detecting data drift and concept drift for ML and statistics applications.
- message-ix — the MESSAGEix integrated assessment model
- message-ix-models — Tools for the MESSAGEix-GLOBIOM family of models
- mgwr — multiscale geographically weighted regression
- minterpy — Python library for multivariate polynomial interpolation.
- mitiq — Mitiq is an open source toolkit for implementing error mitigation techniques on most current intermediate-scale quantum computers.
- mlgw-bns — Accelerating gravitational wave template generation with machine learning.
- mloq_template — Automate project creation following ML best practices.
- mne-connectivity — mne-connectivity: A module for connectivity data analysis with MNE.
- mne-icalabel — MNE-ICALabel: Automatic labeling of ICA components from MEG, EEG and iEEG data with MNE.
- mne-lsl — Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices.
- mne-realtime — A module for real-time data analysis with MNE.
- MOCPy — MOC parsing and manipulation in Python
- modopt — Modular Optimisation tools for soliving inverse problems.
- monkeybread — Analyze cellular niches in single-cell spatial transcriptomics data
- monochrome-viewer — Viewer for monochromatic video data
- morphomapping — Analyze ImageStream Data
- moscot — Multi-omic single-cell optimal transport tools
- moss-rl — A Python library for Reinforcement Learning.
- moyopy — Python binding of Moyo
- mprod-package — Software implementation for tensor-tensor m-product framework
- mqt.bench — MQT Bench - A MQT tool for Benchmarking Quantum Software Tools
- mqt.core — The Backbone of the Munich Quantum Toolkit
- mqt.ddsim — A quantum simulator based on decision diagrams written in C++
- mqt.debugger — A quantum circuit debugging tool
- mqt.predictor — MQT Predictor - A MQT tool for Determining Good Quantum Circuit Compilation Options
- mqt.qao — MQT Quantum Auto Optimizer: Automatic Framework for Solving Optimization Problems with Quantum Computers
- mqt.qcec — A tool for Quantum Circuit Equivalence Checking
- mqt.qecc — QECC - An MQT Tool for Quantum Error Correcting Codes
- mqt.qmap — A tool for Quantum Circuit Mapping
- mqt-qubomaker — A tool for the automatic generation and combination of QUBO formulations for specific problem classes.
- mqt.qudits — A Framework For Mixed-Dimensional Qudit Quantum Computing
- mqt.syrec — A Tool for HDL-based Synthesis of Reversible Circuits
- mrvi — Multi-resolution Variational Inference
- msfc-ccd — A Python library for characterizing and using the CCD cameras developed by Marshall Space Flight Center.
- mubind — ML for biomolecular binding
- multi-slit-solar-explorer — A model of the optical design for the Multi-slit Solar Explorer (MUSE).
- multidms — Joint modeling of multiple deep mutational scanning experiments.
- multigrate — Multigrate: multimodal data integration for single-cell genomics.
- multimil — Multimodal weakly supervised learning to identify disease-specific changes in single-cell atlases
- MUSE-OS — Energy System Model
- mvtk — Model validation toolkit
- MyST-NB — A Jupyter Notebook Sphinx reader built on top of the MyST markdown parser.
- named-arrays — Numpy arrays with labeled axes, similar to xarray but with support for uncertainties
- napari-graph — Fast editable graphs in Python and numba
- napari-prism — A Python package for the inteRactive and Integrated analySis of Multiplexed tissue microarrays
- napari-spatialdata — Interactive visualization of spatial omics data with napari
- ndinterp — N-dimensional interpolation library - python interface
- nemo-text-processing — NeMo text processing for ASR and TTS
- nemo-toolkit — NeMo - a toolkit for Conversational AI
- nibabies — Processing workflows for magnetic resonance images of the brain in infants