DeepStochlog Package For Python

Overview

DeepStochLog

Installation

Installing SWI Prolog

DeepStochLog requires SWI Prolog to run. Run the following commands to install:

sudo apt-add-repository ppa:swi-prolog/stable
sudo apt-get update
sudo apt-get install swi-prolog

Installing DeepStochLog package

To install DeepStochLog itself, run the following command:

pip install deepstochlog

Running the examples

Local dependencies

To see DeepStochLog in action, please first install SWI Prolog (as explained about), as well as the requirements listed in requirements.txt

pip install -r requirements.txt

Datasets

The datasets used in the tasks used to evaluate DeepStochLog can be found in our initial release.

Addition example

To see DeepStochLog in action, navigate to examples/addition and run addition.py.

The neural definite clause grammar specification is provided in addition.pl. The addition(N) predicate specifies/recognises that two handwritten digits N1 and N2 sum to N. The neural probability nn(number, [X], Y, digit) makes the neural network with name number (a MNIST classifier) label input image X with the digit Y.

Credits & Paper citation

If use this work in an academic context, please consider citing the following paper:

The paper is also accepted to AAAI22. Please cite that version of the paper when the proceedings are out.

@article{winters2021deepstochlog,
  title={Deepstochlog: Neural stochastic logic programming},
  author={Winters, Thomas and Marra, Giuseppe and Manhaeve, Robin and De Raedt, Luc},
  journal={arXiv preprint arXiv:2106.12574},
  year={2021}
}
You might also like...
This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters.
This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters.

openmc-plasma-source This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters. The OpenMC sources a

A Python Package for Portfolio Optimization using the Critical Line Algorithm

PyCLA A Python Package for Portfolio Optimization using the Critical Line Algorithm Getting started To use PyCLA, clone the repo and install the requi

HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events globally on daily to subseasonal timescales.

HeatNet HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events glob

NLMpy - A Python package to create neutral landscape models
NLMpy - A Python package to create neutral landscape models

NLMpy is a Python package for the creation of neutral landscape models that are widely used by landscape ecologists to model ecological patterns

QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.
QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.

QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu

Python package provinding tools for artistic interactive applications using AI

Documentation redrawing Python package provinding tools for artistic interactive applications using AI Created by ReDrawing Campinas team for the Open

The hippynn python package - a modular library for atomistic machine learning with pytorch.

The hippynn python package - a modular library for atomistic machine learning with pytorch. We aim to provide a powerful library for the training of a

Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface

pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla

A Python package to process & model ChEMBL data.

insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper

Releases(0.0.1)
Owner
KU Leuven Machine Learning Research Group
KU Leuven Machine Learning Research Group
Allele-specific pipeline for unbiased read mapping(WIP), QTL discovery(WIP), and allelic-imbalance analysis

WASP2 (Currently in pre-development): Allele-specific pipeline for unbiased read mapping(WIP), QTL discovery(WIP), and allelic-imbalance analysis Requ

McVicker Lab 2 Aug 11, 2022
Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation

Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation This is the official repository for our paper Neural Reprojection Error

Hugo Germain 78 Dec 01, 2022
A graph adversarial learning toolbox based on PyTorch and DGL.

GraphWar: Arms Race in Graph Adversarial Learning NOTE: GraphWar is still in the early stages and the API will likely continue to change. 🚀 Installat

Jintang Li 54 Jan 05, 2023
Official Python implementation of the FuzionCoin protocol

PyFuzc Official Python implementation of the FuzionCoin protocol WARNING: Under construction. Use at your own risk. Some functions may not work. Setup

FuzionCoin 3 Jul 07, 2022
Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss (ATVGnet)

Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss (ATVGnet) By Lele Chen , Ross K Maddox, Zhiyao Duan, Chenliang Xu. Unive

Lele Chen 218 Dec 27, 2022
Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation

tf-imle Tensorflow 2 and PyTorch implementation and Jupyter notebooks for Implicit Maximum Likelihood Estimation (I-MLE) proposed in the NeurIPS 2021

NEC Laboratories Europe 69 Dec 13, 2022
CS506-Spring2022 - Code and Slides for Boston University CS 506

CS 506 - Computational Tools for Data Science Code, slides, and notes for Boston

Lance Galletti 17 May 06, 2022
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction

Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction. arxiv This repository contains python scripts for tr

12 Dec 12, 2022
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017

Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req

Seonghyeon Nam 146 Nov 25, 2022
ALFRED - A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

ALFRED A Benchmark for Interpreting Grounded Instructions for Everyday Tasks Mohit Shridhar, Jesse Thomason, Daniel Gordon, Yonatan Bisk, Winson Han,

ALFRED 204 Dec 15, 2022
Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with

Anurag Ranjan 110 Nov 02, 2022
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

Jeya Maria Jose 615 Dec 25, 2022
Blender Python - Node-based multi-line text and image flowchart

MindMapper v0.8 Node-based text and image flowchart for Blender Mindmap with shortcuts visible: Mindmap with shortcuts hidden: Notes This was requeste

SpectralVectors 58 Oct 08, 2022
Parametric Contrastive Learning (ICCV2021)

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

DV Lab 156 Dec 21, 2022
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

Ryan Spring 114 Nov 04, 2022
DANet for Tabular data classification/ regression.

Deep Abstract Networks A PyTorch code implemented for the submission DANets: Deep Abstract Networks for Tabular Data Classification and Regression. Do

Ronnie Rocket 55 Sep 14, 2022
End-To-End Crowdsourcing

End-To-End Crowdsourcing Comparison of traditional crowdsourcing approaches to a state-of-the-art end-to-end crowdsourcing approach LTNet on sentiment

Andreas Koch 1 Mar 06, 2022
Flybirds - BDD-driven natural language automated testing framework, present by Trip Flight

Flybird | English Version 行为驱动开发(Behavior-driven development,缩写BDD),是一种软件过程的思想或者

Ctrip, Inc. 706 Dec 30, 2022
Probabilistic Gradient Boosting Machines

PGBM Probabilistic Gradient Boosting Machines (PGBM) is a probabilistic gradient boosting framework in Python based on PyTorch/Numba, developed by Air

Olivier Sprangers 112 Dec 28, 2022
This code finds bounding box of a single human mouth.

This code finds bounding box of a single human mouth. In comparison to other face segmentation methods, it is relatively insusceptible to open mouth conditions, e.g., yawning, surgical robots, etc. T

iThermAI 4 Nov 27, 2022