360 Repositories
Python probabilistic-modeling Libraries
Top2Vec is an algorithm for topic modeling and semantic search.
Top2Vec is an algorithm for topic modeling and semantic search. It automatically detects topics present in text and generates jointly embedded topic, document and word vectors.
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
ZhuSuan is a Python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
PyStan PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
Functional tensors for probabilistic programming
Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Fast, flexible and easy to use probabilistic modelling in Python.
Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic
Deep universal probabilistic programming with Python and PyTorch
Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl
Library for faster pinned CPU - GPU transfer in Pytorch
SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1
A python library for Bayesian time series modeling
PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W
Probabilistic time series modeling in Python
GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"
FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti
Gaphor is the simple modeling tool
Gaphor Gaphor is a UML and SysML modeling application written in Python. It is designed to be easy to use, while still being powerful. Gaphor implemen
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.
Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations
Modular Probabilistic Programming on MXNet
MXFusion | | | | Tutorials | Documentation | Contribution Guide MXFusion is a modular deep probabilistic programming library. With MXFusion Modules yo
The Python ensemble sampling toolkit for affine-invariant MCMC
emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense
Probabilistic Programming and Statistical Inference in PyTorch
PtStat Probabilistic Programming and Statistical Inference in PyTorch. Introduction This project is being developed during my time at Cogent Labs. The
Supervised domain-agnostic prediction framework for probabilistic modelling
A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
PyStan NOTE: This documentation describes a BETA release of PyStan 3. PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
InferPy: Deep Probabilistic Modeling Made Easy InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top
Deep universal probabilistic programming with Python and PyTorch
Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab
Python Library for Model Interpretation/Explanations
Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Uplift modeling and causal inference with machine learning algorithms
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
Release for Improved Denoising Diffusion Probabilistic Models
improved-diffusion This is the codebase for Improved Denoising Diffusion Probabilistic Models. Usage This section of the README walks through how to t
Gaphor is the simple modeling tool
Gaphor Gaphor is a UML and SysML modeling application written in Python. It is designed to be easy to use, while still being powerful. Gaphor implemen
A multi-entity Transformer for multi-agent spatiotemporal modeling.
baller2vec This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec: A Multi-Entity Transformer For Multi-Agent Spatiotempor
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.
Topic Modelling for Humans
gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ
Beautiful visualizations of how language differs among document types.
Scattertext 0.1.0.0 A tool for finding distinguishing terms in corpora and displaying them in an interactive HTML scatter plot. Points corresponding t
A natural language modeling framework based on PyTorch
Overview PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapi
A Python toolbox for gaining geometric insights into high-dimensional data
"To deal with hyper-planes in a 14 dimensional space, visualize a 3D space and say 'fourteen' very loudly. Everyone does it." - Geoff Hinton Overview
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t
Efficient 3D Backbone Network for Temporal Modeling
VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and
Official code for Score-Based Generative Modeling through Stochastic Differential Equations
Score-Based Generative Modeling through Stochastic Differential Equations This repo contains the official implementation for the paper Score-Based Gen
Efficient neural networks for analog audio effect modeling
micro-TCN Efficient neural networks for audio effect modeling
Topic Modelling for Humans
gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ
Beautiful visualizations of how language differs among document types.
Scattertext 0.1.0.0 A tool for finding distinguishing terms in corpora and displaying them in an interactive HTML scatter plot. Points corresponding t
A natural language modeling framework based on PyTorch
Overview PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapi
A Python toolbox for gaining geometric insights into high-dimensional data
"To deal with hyper-planes in a 14 dimensional space, visualize a 3D space and say 'fourteen' very loudly. Everyone does it." - Geoff Hinton Overview
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
CyGNet This repository reproduces the AAAI'21 paper “Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Network
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t
The Python ensemble sampling toolkit for affine-invariant MCMC
emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense
A natural language modeling framework based on PyTorch
Overview PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapi
Topic Modelling for Humans
gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ
Fast topic modeling platform
The state-of-the-art platform for topic modeling. Full Documentation User Mailing List Download Releases User survey What is BigARTM? BigARTM is a pow
Lightwood is Legos for Machine Learning.
Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu
Machine learning, in numpy
numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Fast, flexible and easy to use probabilistic modelling in Python.
Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic
A Topic Modeling toolbox
Topik A Topic Modeling toolbox. Introduction The aim of topik is to provide a full suite and high-level interface for anyone interested in applying to
Topic Modelling for Humans
gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chap
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl