Python Environment for Bayesian Learning

Last update: Jul 14, 2022

Related tags

Overview

Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Pebl includes the following features:

Can learn with observational and interventional data
Handles missing values and hidden variables using exact and heuristic methods
Provides several learning algorithms; makes creating new ones simple
Has facilities for transparent parallel execution using several cluster and cloud resources
Calculates edge marginals and consensus networks
Presents results in a variety of formats

Pebl has been developed at the Systems Biology Lab at the University of Michigan and in available under a permissive MIT-style license.

Documentation

Pebl is published in the Journal of Machine Learning Research. Please cite the paper if you use Pebl for your work. Abstract and PDF.

Documentation and tutorial in doc/src. Online version available at the Python Package Index.

Owner

Abhik Shah

GitHub Repository

Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2002.11798)

Representation Robustness Evaluations Our implementation is based on code from MadryLab's robustness package and Devon Hjelm's Deep InfoMax. For all t

19 Dec 07, 2022

Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"

gym_multirotor Gym to train reinforcement learning agents on UAV platforms Quadrotor Tiltrotor Requirements This package has been tested on Ubuntu 18.

19 Dec 29, 2022

A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading

A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s

195 Dec 07, 2022

MegEngine implementation of YOLOX

Introduction YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and ind

77 Nov 22, 2022

Face-Recognition-Attendence-System - This face recognition Attendence system using Python

Face-Recognition-Attendence-System I have developed this face recognition Attend

4 May 10, 2022

Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

1 Jan 18, 2022

On Nonlinear Latent Transformations for GAN-based Image Editing - PyTorch implementation

On Nonlinear Latent Transformations for GAN-based Image Editing - PyTorch implementation On Nonlinear Latent Transformations for GAN-based Image Editi

22 Oct 24, 2022

Tackling Obstacle Tower Challenge using PPO & A2C combined with ICM.

Obstacle Tower Challenge using Deep Reinforcement Learning Unity Obstacle Tower is a challenging realistic 3D, third person perspective and procedural

5 Feb 10, 2022

EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This

259 Jan 04, 2023

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

79 Nov 04, 2022

PyTorch implementation for our NeurIPS 2021 Spotlight paper "Long Short-Term Transformer for Online Action Detection".

Long Short-Term Transformer for Online Action Detection Introduction This is a PyTorch implementation for our NeurIPS 2021 Spotlight paper "Long Short

77 Dec 16, 2022

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo

6.6k Jan 06, 2023

Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method (NeurIPS 2021)

Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).

46 Sep 20, 2022

Tracking Progress in Question Answering over Knowledge Graphs

Tracking Progress in Question Answering over Knowledge Graphs Table of contents Question Answering Systems with Descriptions The QA Systems Table cont

47 Jan 02, 2023

Code/data of the paper "Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction" (BMVC2021)

Hand-Object Contact Prediction (BMVC2021) This repository contains the code and data for the paper "Hand-Object Contact Prediction via Motion-Based Ps

13 Nov 07, 2022