Python Predictive-uncertainty Resources

SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving Abstract In this paper, we introduce SalsaNext f

Inferring Spatial Uncertainty in Object Detection A teaser version of the code for the paper Labels Are Not Perfect: Inferring Spatial Uncertainty in

RecSim NG, a probabilistic platform for multi-agent recommender systems simulation. RecSimNG is a scalable, modular, differentiable simulator implemented in Edward2 and TensorFlow. It offers: a powerful, general probabilistic programming language for agent-behavior specification;

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

Sensitivity Analysis Library (SALib) Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking Ning Wang, Wengang Zhou, Jie Wang, and Houqiang Li Accepted by CVPR

Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour

Gelato Bayesian dessert for Lasagne Recent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the be

Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system

======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive

GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,

MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning

Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t

MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning