362 Repositories
Python bayesian-inference Libraries
Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022
PyCRE Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022 Dependencies This project is developed
Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
This folder contains the code for 'Scalable Variational Approaches for Bayesian Causal Discovery'. Installation To install, use conda with conda env c
Bayesian Deep Learning and Deep Reinforcement Learning for Object Shape Error Response and Correction of Manufacturing Systems
Bayesian Deep Learning for Manufacturing 2.0 (dlmfg) Object Shape Error Response (OSER) Digital Lifecycle Management - In Process Quality Improvement
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
Graph Posterior Network This is the official code repository to the paper Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classifica
Rewrite ultralytics/yolov5 v6.0 opencv inference code based on numpy, no need to rely on pytorch
Rewrite ultralytics/yolov5 v6.0 opencv inference code based on numpy, no need to rely on pytorch; pre-processing and post-processing using numpy instead of pytroch.
Python implementation of Bayesian optimization over permutation spaces.
Bayesian Optimization over Permutation Spaces This repository contains the source code and the resources related to the paper "Bayesian Optimization o
[NeurIPS-2021] Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici
Randomisation-based inference in Python based on data resampling and permutation.
Randomisation-based inference in Python based on data resampling and permutation.
[NeurIPS-2021] Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici
A Model for Natural Language Attack on Text Classification and Inference
TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re
Code for the paper "BERT Loses Patience: Fast and Robust Inference with Early Exit".
Patience-based Early Exit Code for the paper "BERT Loses Patience: Fast and Robust Inference with Early Exit". NEWS: We now have a better and tidier i
Source code for "FastBERT: a Self-distilling BERT with Adaptive Inference Time".
FastBERT Source code for "FastBERT: a Self-distilling BERT with Adaptive Inference Time". Good News 2021/10/29 - Code: Code of FastPLM is released on
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
DeeBERT This is the code base for the paper DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference. Code in this repository is also available
This repository contains the code for "Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference"
Pattern-Exploiting Training (PET) This repository contains the code for Exploiting Cloze Questions for Few-Shot Text Classification and Natural Langua
[NeurIPS '21] Adversarial Attacks on Graph Classification via Bayesian Optimisation (GRABNEL)
Adversarial Attacks on Graph Classification via Bayesian Optimisation @ NeurIPS 2021 This repository contains the official implementation of GRABNEL,
This repository is for the preprint "A generative nonparametric Bayesian model for whole genomes"
BEAR Overview This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which pro
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
LMPBT Supplementary code for the Paper entitled ``Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models"
Bayesian inference for Permuton-induced Chinese Restaurant Process (NeurIPS2021).
Permuton-induced Chinese Restaurant Process Note: Currently only the Matlab version is available, but a Python version will be available soon! This is
High performance Cross-platform Inference-engine, you could run Anakin on x86-cpu,arm, nv-gpu, amd-gpu,bitmain and cambricon devices.
Anakin2.0 Welcome to the Anakin GitHub. Anakin is a cross-platform, high-performance inference engine, which is originally developed by Baidu engineer
Real-time VIBE: Frame by Frame Inference of VIBE (Video Inference for Human Body Pose and Shape Estimation)
Real-time VIBE Inference VIBE frame-by-frame. Overview This is a frame-by-frame inference fork of VIBE at [https://github.com/mkocabas/VIBE]. Usage: i
Low-code/No-code approach for deep learning inference on devices
EzEdgeAI A concept project that uses a low-code/no-code approach to implement deep learning inference on devices. It provides a componentized framewor
Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".
Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer
Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model
Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model
Large scale and asynchronous Hyperparameter Optimization at your fingertip.
Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option
An index of algorithms for learning causality with data
awesome-causality-algorithms An index of algorithms for learning causality with data. Please cite our survey paper if this index is helpful. @article{
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Blitz - Bayesian Layers in Torch Zoo BLiTZ is a simple and extensible library to create Bayesian Neural Network Layers (based on whats proposed in Wei
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De
PointPillars inference with TensorRT
A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar.
Self-Supervised Document-to-Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
A collection of inference modules for fastai2
fastinference A collection of inference modules for fastai including inference speedup and interpretability Install pip install fastinference There ar
A Python package for causal inference using Synthetic Controls
Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3
Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
Generalized Random Forests
generalized random forests A pluggable package for forest-based statistical estimation and inference. GRF currently provides non-parametric methods fo
Bayesian Additive Regression Trees For Python
BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART
TransMorph: Transformer for Medical Image Registration
TransMorph: Transformer for Medical Image Registration keywords: Vision Transformer, Swin Transformer, convolutional neural networks, image registrati
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl
Topic Inference with Zeroshot models
zeroshot_topics Table of Contents Installation Usage License Installation zeroshot_topics is distributed on PyPI as a universal wheel and is available
Source code for our paper "Do Not Trust Prediction Scores for Membership Inference Attacks"
Do Not Trust Prediction Scores for Membership Inference Attacks Abstract: Membership inference attacks (MIAs) aim to determine whether a specific samp
Code for "Universal inference meets random projections: a scalable test for log-concavity"
How to use this repository This repository contains code to replicate the results of "Universal inference meets random projections: a scalable test fo
Machine Learning Privacy Meter: A tool to quantify the privacy risks of machine learning models with respect to inference attacks, notably membership inference attacks
ML Privacy Meter Machine learning is playing a central role in automated decision making in a wide range of organization and service providers. The da
Bayesian Generative Adversarial Networks in Tensorflow
Bayesian Generative Adversarial Networks in Tensorflow This repository contains the Tensorflow implementation of the Bayesian GAN by Yunus Saatchi and
Adversarially Learned Inference
Adversarially Learned Inference Code for the Adversarially Learned Inference paper. Compiling the paper locally From the repo's root directory, $ cd p
Lightweight Python library for adding real-time object tracking to any detector.
Norfair is a customizable lightweight Python library for real-time 2D object tracking. Using Norfair, you can add tracking capabilities to any detecto
Ladder Variational Autoencoders (LVAE) in PyTorch
Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at
Hummingbird compiles trained ML models into tensor computation for faster inference.
Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Kalman and Bayesian Filters in Python Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written
Extracting and filtering paraphrases by bridging natural language inference and paraphrasing
nli2paraphrases Source code repository accompanying the preprint Extracting and filtering paraphrases by bridging natural language inference and parap
This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our paper "Accounting for Gaussian Process Imprecision in Bayesian Optimization"
Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our
Python package for causal inference using Bayesian structural time-series models.
Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI
A Python package for modular causal inference analysis and model evaluations
Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Dragonfly is an open source python library for scalable Bayesian optimisation.
Dragonfly is an open source python library for scalable Bayesian optimisation. Bayesian optimisation is used for optimising black-box functions whose
PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices.
PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With
A Python training and inference implementation of Yolov5 helmet detection in Jetson Xavier nx and Jetson nano
yolov5-helmet-detection-python A Python implementation of Yolov5 to detect head or helmet in the wild in Jetson Xavier nx and Jetson nano. In Jetson X
Official implementation of "Membership Inference Attacks Against Self-supervised Speech Models"
Introduction Official implementation of "Membership Inference Attacks Against Self-supervised Speech Models". In this work, we demonstrate that existi
v objective diffusion inference code for JAX.
v-diffusion-jax v objective diffusion inference code for JAX, by Katherine Crowson (@RiversHaveWings) and Chainbreakers AI (@jd_pressman). The models
Repo for Photon-Starved Scene Inference using Single Photon Cameras, ICCV 2021
Photon-Starved Scene Inference using Single Photon Cameras ICCV 2021 Arxiv Project Video Bhavya Goyal, Mohit Gupta University of Wisconsin-Madison Abs
Inference pipeline for our participation in the FeTA challenge 2021.
feta-inference Inference pipeline for our participation in the FeTA challenge 2021. Team name: TRABIT Installation Download the two folders in https:/
Recursive Bayesian Networks
Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"
GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
causal-bald | Abstract | Installation | Example | Citation | Reproducing Results DUE An implementation of the methods presented in Causal-BALD: Deep B
A modular, research-friendly framework for high-performance and inference of sequence models at many scales
T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of
Spert NLP Relation Extraction API deployed with torchserve for inference
SpERT torchserve Spert_torchserve is the Relation Extraction model (SpERT)Span-based Entity and Relation Transformer API deployed with pytorch/serve.
Generalized and Efficient Blackbox Optimization System.
OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio
Framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample resolution
Sample-specific Bayesian Networks A framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample or per-patient re
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's algorithm.
Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil
This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging" that has been accepted to NeurIPS 2021.
Dugh-NeurIPS-2021 This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroi
Bayesian Optimization Library for Medical Image Segmentation.
bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im
Monocular 3D pose estimation. OpenVINO. CPU inference or iGPU (OpenCL) inference.
human-pose-estimation-3d-python-cpp RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used) 1. Run 1-1. RealSenseD435 (RGB) 480x640 + CPU
Code for "Discovering Non-monotonic Autoregressive Orderings with Variational Inference" (paper and code updated from ICLR 2021)
Discovering Non-monotonic Autoregressive Orderings with Variational Inference Description This package contains the source code implementation of the
IndoNLI: A Natural Language Inference Dataset for Indonesian
IndoNLI: A Natural Language Inference Dataset for Indonesian This is a repository for data and code accompanying our EMNLP 2021 paper "IndoNLI: A Natu
Implementation of several Bayesian multi-target tracking algorithms, including Poisson multi-Bernoulli mixture filters for sets of targets and sets of trajectories. The repository also includes the GOSPA metric and a metric for sets of trajectories to evaluate performance.
This repository contains the Matlab implementations for the following multi-target filtering/tracking algorithms: - Folder PMBM contains the implemen
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled Time Series presented at Causal Analysis Workshop 2021.
signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled
Classifies galaxy morphology with Bayesian CNN
Zoobot Zoobot classifies galaxy morphology with deep learning. This code will let you: Reproduce and improve the Galaxy Zoo DECaLS automated classific
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
Bayesian optimisation library developped by Huawei Noah's Ark Library
Bayesian Optimisation Research This directory contains official implementations for Bayesian optimisation works developped by Huawei R&D, Noah's Ark L
A SageMaker Projects template to deploy a model from Model Registry, choosing your preferred method of deployment among async (Asynchronous Inference), batch (Batch Transform), realtime (Real-time Inference Endpoint). More to be added soon!
SageMaker Projects: Multiple Choice Deployment A SageMaker Projects template to deploy a model from Model Registry, choosing your preferred method of
Bayesian Meta-Learning Through Variational Gaussian Processes
vmgp This is the repository of Vivek Myers and Nikhil Sardana for our CS 330 final project, Bayesian Meta-Learning Through Variational Gaussian Proces
A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, color transfer, and gradient flow.
BoMb-OT Python3 implementation of the papers On Transportation of Mini-batches: A Hierarchical Approach and Improving Mini-batch Optimal Transport via
On-device speech-to-intent engine powered by deep learning
Rhino Made in Vancouver, Canada by Picovoice Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a giv
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
High-quality implementations of standard and SOTA methods on a variety of tasks.
Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine
PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)
PixelPyramids: Exact Inference Models from Lossless Image Pyramids This repository contains the PyTorch implementation of the paper PixelPyramids: Exa
Membership Inference Attack against Graph Neural Networks
MIA GNN Project Starter If you meet the version mismatch error for Lasagne library, please use following command to upgrade Lasagne library. pip insta
Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning
Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning Update (September 18th, 2021) A supporting document de
This repository outlines deploying a local Kubeflow v1.3 instance on microk8s and deploying a simple MNIST classifier using KFServing.
Zero to Inference with Kubeflow Getting Started This repository houses all of the tools, utilities, and example pipeline implementations for exploring
Companion code for the paper "An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence" (NeurIPS 2021)
ReLU-GP Residual (RGPR) This repository contains code for reproducing the following NeurIPS 2021 paper: @inproceedings{kristiadi2021infinite, title=
Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations.
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
Acoustic mosquito detection code with Bayesian Neural Networks
HumBugDB Acoustic mosquito detection with Bayesian Neural Networks. Extract audio or features from our large-scale dataset on Zenodo. This repository
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.
PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
Code for Environment Inference for Invariant Learning (ICML 2020 UDL Workshop Paper)
Environment Inference for Invariant Learning This code accompanies the paper Environment Inference for Invariant Learning, which appears at ICML 2021.
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations Requirements The code is implemented in Python and requires