Python Gaussian-distribution Resources

Generalized Out-of-Distribution Detection: A Survey 1. Overview This repository is with our survey paper: Title: Generalized Out-of-Distribution Detec

ec2-imagebuilder-ami-share CloudFormation template and CDK stack that contains a CustomResource with Lambda function to allow the setting of the targe

Class HiddenMarkovModel HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow 2.0 Installatio

Joint Gaussian Graphical Model Estimation: A Survey Test Models Fused graphical lasso [1] Group graphical lasso [1] Graphical lasso [1] Doubly joint s

GMM-CNN This code package implements the modeling of CNN layers activity with Gaussian mixture model and Inference Graphs visualization technique from

Generalized Out-of-Distribution Detection: A Survey 1. Overview This repository is with our survey paper: Title: Generalized Out-of-Distribution Detec

vmgp This is the repository of Vivek Myers and Nikhil Sardana for our CS 330 final project, Bayesian Meta-Learning Through Variational Gaussian Proces

TWIST: Self-Supervised Learning by Estimating Twin Class Distributions Codes and pretrained models for TWIST: @article{wang2021self, title={Self-Sup

Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (

OOD Detection Load conda environment conda env create -f environment.yml or install requirements: while read requirement; do conda install --yes $requ

SS-GMM Implementation of ICCV 2021 oral paper -- Self-Supervised Image Prior Learning with GMM from a Single Noisy Image with supplementary material R

BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer

Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t

Uncertainty-based OOD detection Exploring the link between uncertainty estimates obtained by "exact" Bayesian inference and out-of-distribution (OOD)

[TensorFlow 2] Variational Inference with Normalizing Flows TensorFlow implementation of "Variational Inference with Normalizing Flows" [1] Concept Co

Python package for probability density function fitting of univariate distributions of non-censored data

Learning Confidence Estimates for Neural Networks This repository contains the code for the paper Learning Confidence for Out-of-Distribution Detectio

Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples This project is for the paper "Training Confidence-Calibrated Clas

Overview PowerGym is a Gym-like environment for Volt-Var control in power distribution systems. The Volt-Var control targets minimizing voltage violat

TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Markovflow Documentation | Tutorials | API reference | Slack What does Markovflow do? Markovflow is a Python library for time-series analysis via prob

AAGCN-ACSA EMNLP 2021 Introduction This repository was used in our paper: Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment An

Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

ood-text-emnlp Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them" Files fine_tune.py is used to finetune the GPT-2 mo

StableNet StableNet is a deep stable learning method for out-of-distribution generalization. This is the official repo for CVPR21 paper "Deep Stable L

Amplitude-Phase Recombination (ICCV'21) Official PyTorch implementation of "Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neur

Contra-OOD Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers. Requirements PyTorch Transformers datasets

Fishr: Invariant Gradient Variances for Out-of-distribution Generalization Official PyTorch implementation of the Fishr regularization for out-of-dist

LibreGaming Python Program that downloads gaming required packages based on your Linux Distribution. Table of contents Distributions Prerequisites Dep

Multi-speaker DGP This repository provides official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch. O

SCOOD-UDG (ICCV 2021) This repository is the official implementation of the paper: Semantically Coherent Out-of-Distribution Detection Jingkang Yang,

CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm

CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm

ODIN: Out-of-Distribution Detector for Neural Networks This is a PyTorch implementation for detecting out-of-distribution examples in neural networks.

Daft-Exprt - PyTorch Implementation PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis The

A linear equation solver using gaussian elimination. Implemented for fun and learning/teaching. The solver will solve equations of the type: A can be

FOOD - Fast OOD Detector Pytorch implamentation of the confernce peper FOOD arxiv link. Abstract Deep neural networks (DNNs) perform well at classifyi

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI Gym toolkit.

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

OOD-detection-using-OECC This repository contains the essential code for the paper Outlier Exposure with Confidence Control for Out-of-Distribution De

Diverse Semantic Image Synthesis via Probability Distribution Modeling (CVPR 2021) Paper Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu,

Patch-Rotation(PatchRot) Patch Rotation: A Self-Supervised Auxiliary Task for Robustness and Accuracy of Supervised Models Submitted to Neurips2021 To

Deep Conditional Gaussian Mixture Model for Constrained Clustering. This repository holds the code for the paper Deep Conditional Gaussian Mixture Mod

Out-of-distribution Generalization Investigation on Vision Transformers This repository contains PyTorch evaluation code for Delving Deep into the Gen

Overview This repository contains some of the scripts we have used for running our airdrop campaigns and other distributions. Initially, all of these

Adversarial Reciprocal Points Learning for Open Set Recognition Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Se

JupyterLite is a JupyterLab distribution that runs entirely in the browser built from the ground-up using JupyterLab components and extensions.

Spherical Gaussian Optimization This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization. This code has b

Multi-Output Gaussian Process Toolkit Paper - API Documentation - Tutorials & Examples The Multi-Output Gaussian Process Toolkit is a Python toolkit f

Matern Gaussian Processes on Graphs This repo provides an extension for gpflow with Matérn kernels, inducing variables and trainable models implemente

Vaccine Availability Notifier Project Description Checks for Vaccine Availability at your district and notifies you using E-mail every 10 mins. Kindly

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

Adversarial Long-Tail This repository contains the PyTorch implementation of the paper: Adversarial Robustness under Long-Tailed Distribution, CVPR 20

Implementation of "Distribution Alignment: A Unified Framework for Long-tail Visual Recognition"(CVPR 2021)

⚡ OPAL ⚡ Open Policy Administration Layer OPAL is an administration layer for Open Policy Agent (OPA), detecting changes to both policy and policy dat

Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.

CaDDN CaDDN is a monocular-based 3D object detection method. This repository is based off of [OpenPCDet]. Categorical Depth Distribution Network for M

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Distribution Analyser Distribution Analyser is a Web App that allows you to interactively explore continuous distributions from SciPy and fit distribu

World's best free and open source ERP.

Likelihood-Regret Official implementation of Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020. T

Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

Bayesian Optimization Pure Python implementation of bayesian global optimization with gaussian processes. PyPI (pip): $ pip install bayesian-optimizat

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

Tutor: the docker-based Open edX distribution designed for peace of mind Tutor is a docker-based Open edX distribution, both for production and local

Mailu is a simple yet full-featured mail server as a set of Docker images. It is free software (both as in free beer and as in free speech), open to s

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

wheel This library is the reference implementation of the Python wheel packaging standard, as defined in PEP 427. It has two different roles: A setupt

PyOxidizer PyOxidizer is a utility for producing binaries that embed Python. The over-arching goal of PyOxidizer is to make complex packaging and dist

Spyder is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It offers a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package.

WILDS is a benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications, from tumor identification to wildlife monitoring to poverty mapping.

numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install

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