Python Stochastic-variational-inference Resources

Adaptation through prediction: multisensory active inference torque control Submitted to IEEE Transactions on Cognitive and Developmental Systems Abst

vq-wav2vec inference A minimal code for fairseq vq-wav2vec model inference. Runs without installing the fairseq toolkit and its dependencies. Usage ex

PyTorch implementation of normalizing flow models

Isaac ROS DNN Inference Overview This repository provides two NVIDIA GPU-accelerated ROS2 nodes that perform deep learning inference using custom mode

Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.

Translates LinkML schemas into Datalog programs and executes them using Souffle, enabling advanced validation and inference over instance data

Visual Adversarial Imitation Learning using Variational Models (VMAIL) This is the official implementation of the NeurIPS 2021 paper. Project website

PyCRE Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022 Dependencies This project is developed

Junction Tree Variational Autoencoder for Molecular Graph Generation Official implementation of our Junction Tree Variational Autoencoder https://arxi

This folder contains the code for 'Scalable Variational Approaches for Bayesian Causal Discovery'. Installation To install, use conda with conda env c

SLAMP: Stochastic Latent Appearance and Motion Prediction Official implementation of the paper SLAMP: Stochastic Latent Appearance and Motion Predicti

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.

Pytorch implementation of VQVAE. This paper combines 2 tricks: Vector Quantization (check out this amazing blog for better understanding.) Straight-Th

jax-variational-diffwave Jax/Flax implementation of Variational-DiffWave. (Zhifeng Kong et al., 2020, Diederik P. Kingma et al., 2021.) DiffWave with

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.

Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici

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

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

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 This is the code base for the paper DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference. Code in this repository is also available

Pattern-Exploiting Training (PET) This repository contains the code for Exploiting Cloze Questions for Few-Shot Text Classification and Natural Langua

Experiments How to reproduce experimental results of Stochastic bandits with groups of similar arms submitted paper ? Section 5 of the paper To reprod

Permuton-induced Chinese Restaurant Process Note: Currently only the Matlab version is available, but a Python version will be available soon! This is

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 Inference VIBE frame-by-frame. Overview This is a frame-by-frame inference fork of VIBE at [https://github.com/mkocabas/VIBE]. Usage: i

EzEdgeAI A concept project that uses a low-code/no-code approach to implement deep learning inference on devices. It provides a componentized framewor

Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh

Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer

awesome-causality-algorithms An index of algorithms for learning causality with data. Please cite our survey paper if this index is helpful. @article{

Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera

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

A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar.

Contrastively Disentangled Sequential Variational Audoencoder (C-DSVAE) Overview This is the implementation for our C-DSVAE, a novel self-supervised d

Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro

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.

fastinference A collection of inference modules for fastai including inference speedup and interpretability Install pip install fastinference There ar

Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim

Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are

generalized random forests A pluggable package for forest-based statistical estimation and inference. GRF currently provides non-parametric methods fo

Score-Based Generative Modeling through Stochastic Differential Equations This repo contains a PyTorch implementation for the paper Score-Based Genera

zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl

zeroshot_topics Table of Contents Installation Usage License Installation zeroshot_topics is distributed on PyPI as a universal wheel and is available

Do Not Trust Prediction Scores for Membership Inference Attacks Abstract: Membership inference attacks (MIAs) aim to determine whether a specific samp

How to use this repository This repository contains code to replicate the results of "Universal inference meets random projections: a scalable test fo

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

alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi

Experimental code for paper: Generative Adversarial Networks as Variational Training of Energy Based Models, under review at ICLR 2017 requirements: T

Adversarially Learned Inference Code for the Adversarially Learned Inference paper. Compiling the paper locally From the repo's root directory, $ cd p

cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut

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) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

Open-KG-canonicalization The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational

Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th

nli2paraphrases Source code repository accompanying the preprint Extracting and filtering paraphrases by bridging natural language inference and parap

Stochastic Extragradient: General Analysis and Improved Rates This repository is the official implementation of the paper "Stochastic Extragradient: G

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

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

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

What is Viridicle? Viridicle is a library for simulating stochastic graphical ecological models. It implements the continuous time models described in

Introduction Official implementation of "Membership Inference Attacks Against Self-supervised Speech Models". In this work, we demonstrate that existi

collision_risk_estimation Collision risk estimation using stochastic motion models. This is a new approach, based on stochastic models, to predict the

This package is a python library with tools for the Molecular Simulation - Software Gromos. It allows you to easily set up, manage and analyze simulations in python.

v-diffusion-jax v objective diffusion inference code for JAX, by Katherine Crowson (@RiversHaveWings) and Chainbreakers AI (@jd_pressman). The models

Photon-Starved Scene Inference using Single Photon Cameras ICCV 2021 Arxiv Project Video Bhavya Goyal, Mohit Gupta University of Wisconsin-Madison Abs

Conditional Variational Capsule Network for Open Set Recognition This repository hosts the official code related to "Conditional Variational Capsule N

Dual Parameterization of Sparse Variational Gaussian Processes Documentation | Notebooks | API reference Introduction This repository is the official

feta-inference Inference pipeline for our participation in the FeTA challenge 2021. Team name: TRABIT Installation Download the two folders in https:/

Introduction This script trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI. In order to run this

Stochastic Scene-Aware Motion Prediction [Project Page] [Paper] Description This repository contains the training code for MotionNet and GoalNet of SA

GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context

T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of

SpERT torchserve Spert_torchserve is the Relation Extraction model (SpERT)Span-based Entity and Relation Transformer API deployed with pytorch/serve.

Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

Dugh-NeurIPS-2021 This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroi

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

Official repository of the paper (UAI 2021) "A Variational Approximation for Analyzing the Dynamics of Panel Data", Mixed Effect Neural ODE. Panel dat

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 This is a repository for data and code accompanying our EMNLP 2021 paper "IndoNLI: A Natu

VACA Code repository for the paper "VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries (arXiv)". The impleme

Conditioning Sparse Variational Gaussian Processes for Online Decision-making This repository contains a PyTorch and GPyTorch implementation of the pa

SGD-Linear-Regressor Iterative stochastic gradient descent (SGD) linear regressor with regularization Dataset: Kaggle “Graduate Admission 2” https://w

Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica

Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th

Variational Filtering To run phi learning on linear gaussian (Fig1a) python linear_gaussian_phi_learning.py To run phi and theta learning on linear g

Unsupervised Document Expansion for Information Retrieval with Stochastic Text Generation Official Code Repository for the paper "Unsupervised Documen

PyTorch Autoencoders Implementing a Variational Autoencoder (VAE) Series in Pytorch. Inspired by this repository Model List check model paper conferen

Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders Getting Started Install requirements with Anaconda: conda env c

About Repository This repository contains code used for plots in NeurIPS 2021 paper 'Stochastic Multi-Armed Bandits with Control Variates.' About Code

signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled

DU-VAE This is the pytorch implementation of the paper "Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness" Acknowledgement

SageMaker Projects: Multiple Choice Deployment A SageMaker Projects template to deploy a model from Model Registry, choosing your preferred method of

Stochastic Gradient Trees - Python Stochastic Gradient Trees1 by Henry Gouk, Bernhard Pfahringer, and Eibe Frank implementation in Python. Based on th

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