Reverse Dependencies of seaborn
The following projects have a declared dependency on seaborn:
- biostatistics — An intuitive app for statistical analysis
- biosynonyms — A decentralized database of synonyms for biomedical concepts and entities.
- biotuner — Time series harmonic analysis for adaptive tuning systems and microtonal exploration
- biovector — Scientific work out app
- bioversions — What's the current version for each biological database?
- birdset — BirdSet: A multi-task benchmark and data pipeline for deep learning based avian bioacoustics
- birt-gd — BIRT is an implementation of Beta3-irt using gradient descent.
- bitcoinabuse-monitor — utility tool for measuring bot activity on bitcoinabuse.com
- Bitmasher — Bit rotational encryption with steganography
- bivariate — This package contains methods that assist in performing bivariate analysis of datasets.
- BJA-plot-helpers — Convenience functions for plotting with matplotlib and seaborn
- bkh-pytorch-utils — A rapid prototyping tool for MONAI & PyTorch Lightning
- bktest — bktest - A simple backtester by CrunchDAO
- black-it — black-it: Black-box abm calibration kit
- blackbeard2109 — This library is designed for people who need to optimize time in an agile way with an ease of understanding and could
- blechpy — Package for exrtacting, processing and analyzing Intan and OpenEphys data
- blending-toolkit — Blending ToolKit
- bliz — Utilities for dataframes
- blksheep — A package for differential extreme values analysis
- blobBgone — A lightweight tool to remove blob artifacts from 2D/3D point cloud data as produced by MINFLUX
- blobcity — Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
- blockmatrix — Utilities to handle blockmatrices, especially covariance matrices.
- blocksnet — Package provides methods of master plan requirements automated generation for urban areas
- bluecast — A lightweight and fast automl framework
- blueetl — Multiple simulations analysis tool
- bmiselect — Bayesian MI-LASSO for variable selection on multiply-imputed data.
- bmmltools — BioMaterial Machine Learning tools (bmmltools), package to do machine learning with large binary 3d images
- bmr4pml — Bayesian model reduction for probabilistic machine learning
- bnpm — A library of useful modules for data analysis.
- boar-pv — High throughput parameter extraction and experimental design with Bayesian optimization
- bocoel — Bayesian Optimization as a Coverage Tool for Evaluating Large Language Models
- bocpd — Bayesian Online Changepoint Detection
- BOFdat — Package to generate biomass objective function stoichiometric coefficients from experimental data
- boilercv — Computer vision routines suitable for nucleate pool boiling bubble analysis
- boilerdaq — Data processing pipeline for a nucleate pool boiling apparatus.
- boilerdata — Data processing pipeline for a nucleate pool boiling apparatus.
- bolero — sequence
- bonsai-tree — Bayesian Optimization + Gradient Boosted Trees
- booleabayes — A suite for network inference from transcriptomics data
- bootstrap.pytorch — High level framework for starting Deep Learning projects
- borec-tool — Tool for visualization and analysis of hyperspectral data
- BorutaShap — A feature selection algorithm.
- boston-housing-prediction — Predict housing prices in boston.
- boxsers — Python package that provides a full range of functionality to process and analyze vibrational spectra (Raman, SERS, FTIR, etc.).
- boxx — Tool-box for efficient build and debug in Python. Especially for Scientific Computing and Computer Vision.
- bp-neurotools — General helper functions for working with neuroimaging data.
- bpnet — BPNet: toolkit to learn motif synthax from high-resolution functional genomics data using convolutional neural networks
- bpnet-lite — bpnet-lite is a minimal implementation of BPNet, a neural network aimed at interpreting regulatory activity of the genome.
- BPrune — Bayesiean Neural Network Pruning Library
- brain-pred-toolbox — The Brain Predictability toolbox (BPt) is a Python based machine learning library designed to work with a range of neuroimaging data. Warning: Not actively maintained as of 11/30/22.
- brainbox-ibl — International Brain Laboratory data pipeline library
- BrainCog — BrainCog is an open source spiking neural network based brain-inspired cognitive intelligence engine for Brain-inspired Artificial Intelligence and brain simulation. More information on braincog can be found on its homepage http://www.brain-cog.network/
- Braindecode — Deep learning software to decode EEG, ECG or MEG signals
- brainlit — Code to process and analyze brainlit data
- brainsurfy — brainsurfy
- brancher — A user-centered Python package for differentiable probabilistic inference
- brebsML — Toutes les librairies que nous utiliseront pour ce comité
- breizhcrops — A Satellite Time Series Dataset for Crop Type Identification
- brickstudy — A package for analysis of MRI
- brioche-enrichment — Bayesian tests for set enrichment.
- Broad-GenePy — A useful module for any CompBio
- broadsteel-datascience — BroadSteel_DataScience
- bruno-util — Catch-all package for utilities useful to Bruno Beltran
- bs-ds — A collection of tools from bootcamp.
- bs-python-utils — my Python utilities
- bs-synth — A population synthesis code for the blazar sequence
- bsxplorer — Analytical framework for BS-seq data comparison and visualization
- btc-sentiment-analysis — A small sentiment analysis library for bitcoin
- BuckFit — Modular potential fitting code for classical MD buckingham potentials
- buildings-bench — Large-scale pretraining and benchmarking for short-term load forecasting.
- buildlytics-test-3 — EDA Package Test
- buildml — Let's make building machine learning models the complex way, easy.
- bumbleview — Convert physical spectra to excitation potential in insect eyes
- bundestag — Download, parse and analyse votes in the german federal parliament, aka 'Bundestag'
- burnt-ends — A Python package containing modular, well-tested, utility and statistical functions handy for scientific computing and analysis.
- buscoplotpy — A Python library for BUSCO data visualization.
- BYOST — BYOST (Build Your Own Spectral Template)
- c2s2-standard — Consensus clustering for a number of individuals with HPO terms or phenopackets.
- c5py — Analysis and visualization tools for the Augmented Reality-based Corpus (ARbC). This corpus has been created in the research project 'Alignment in AR-based cooperation' which was a part of the Collaborative Research Centre 'Alignment in Communication' (CRC 673) under the project code C5.
- c7m — Module for analysis of high-throughput, fluorescence, wide-field microscopy images.
- cactice — computing agricultural crop lattices
- CADETMatch — CADETMatch is a parameter estimation and error modeling library for CADET
- cafe — Classifying Antibodies for Expression
- cagraph — A package to generate graphs from calcium imaging data of neural activity.
- calh — Calendar Heatmap
- CalibrationCurve — A collection of functions that streamline the process of creating calibration curves using Python.
- CalSciPy — A toolbox for analyzing, designing, and visualizing multiphoton imaging & optogenetics experiments.
- CalSim — Simulator package for Berkeley robotics course.
- cami-amber — AMBER: Assessment of Metagenome BinnERs
- cami-opal — OPAL: Open-community Profiling Assessment tooL
- CAMIViz — A collection of tools to visualize CAMI profiling outputs
- canary-sefi — Canary SEFI is a framework for evaluating the adversarial robustness of deep learning-based image recognition models.
- candis — A data mining suite for DNA Microarrays.
- candycan — can wrapper for applications
- Cannai — data visualization for machine learning
- canonical-sets — Exposing Algorithmic Bias with Canonical Sets.
- cansig — Discovering de novo shared transcriptional programs in single cancer cells
- capcruncher — An end-to-end solution for processing Capture-C, Tri-C and Tiled-C data
- capstone-text-mining — Capstone Text Mining Techniques
- captain-project — Conservation Area Prioritization Through Artificial INtelligence