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
sense-py-AnishaBaishya created by GitHub Classroom

Compute Statistics Here we compute statistics for a bunch of numbers. This project uses the unittest framework to test functionality. Pass the tests T

1 Oct 21, 2021
😮The official implementation of "CoNeRF: Controllable Neural Radiance Fields" 😮

CoNeRF: Controllable Neural Radiance Fields This is the official implementation for "CoNeRF: Controllable Neural Radiance Fields" Project Page Paper V

Kacper Kania 61 Dec 24, 2022
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes

Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes

111 Dec 29, 2022
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip)

Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip) Introduction TL;DR: We propose an efficient and trainabl

17 Dec 01, 2022
One implementation of the paper "DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing".

Introduction One implementation of the paper "DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing". Users

seq-to-mind 18 Dec 11, 2022
Install alphafold on the local machine, get out of docker.

AlphaFold This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP

Kui Xu 73 Dec 13, 2022
Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions"

Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor

yifan 10 Oct 18, 2022
How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop

Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer

Tuomas Oikarinen 42 Dec 10, 2022
Spam your friends and famly and when you do your famly will disown you and you will have no friends.

SpamBot9000 Spam your friends and family and when you do your family will disown you and you will have no friends. Terms of Use Disclaimer: Please onl

DJ15 0 Jun 09, 2022
Pytorch implementation of the Variational Recurrent Neural Network (VRNN).

VariationalRecurrentNeuralNetwork Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data. Th

emmanuel 251 Dec 17, 2022
Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic [Paper] [Colab is coming soon] Approach Example Usage To r

170 Jan 03, 2023
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.

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.

P-Lambda 437 Dec 30, 2022
working repo for my xumx-sliCQ submissions to the ISMIR 2021 MDX

Music Demixing Challenge - xumx-sliCQ This repository is the GitHub mirror of my working submission repository for the AICrowd ISMIR 2021 Music Demixi

4 Aug 25, 2021
Multiple-Object Tracking with Transformer

TransTrack: Multiple-Object Tracking with Transformer Introduction TransTrack: Multiple-Object Tracking with Transformer Models Training data Training

Peize Sun 537 Jan 04, 2023
Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].

Time2box Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].

LingCai 4 Aug 23, 2022
Constraint-based geometry sketcher for blender

Constraint-based sketcher addon for Blender that allows to create precise 2d shapes by defining a set of geometric constraints like tangent, distance,

1.7k Dec 31, 2022
Management Dashboard for Torchserve

Torchserve Dashboard Torchserve Dashboard using Streamlit Related blog post Usage Additional Requirement: torchserve (recommended:v0.5.2) Simply run:

Ceyda Cinarel 103 Dec 10, 2022
Very Deep Convolutional Networks for Large-Scale Image Recognition

pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo

Justin Johnson 217 Dec 05, 2022
BOVText: A Large-Scale, Multidimensional Multilingual Dataset for Video Text Spotting

BOVText: A Large-Scale, Bilingual Open World Dataset for Video Text Spotting Updated on December 10, 2021 (Release all dataset(2021 videos)) Updated o

weijiawu 47 Dec 26, 2022
A python library to artfully visualize Factorio Blueprints and an interactive web demo for using it.

Factorio Blueprint Visualizer I love the game Factorio and I really like the look of factories after growing for many hours or blueprints after tweaki

Piet Brömmel 124 Jan 07, 2023