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
A plug-and-play library for neural networks written in Python

A plug-and-play library for neural networks written in Python!

Dimos Michailidis 2 Jul 16, 2022
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

Yixuan Su 79 Nov 04, 2022
Sound Source Localization for AI Grand Challenge 2021

Sound-Source-Localization Sound Source Localization study for AI Grand Challenge 2021 (sponsored by NC Soft Vision Lab) Preparation 1. Place the data-

sanghoon 19 Mar 29, 2022
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

AstraZeneca 79 Jan 05, 2023
Sparse Physics-based and Interpretable Neural Networks

Sparse Physics-based and Interpretable Neural Networks for PDEs This repository contains the code and manuscript for research done on Sparse Physics-b

28 Jan 03, 2023
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018

Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo

Wayne Hung 464 Dec 19, 2022
A multi-mode modulator for multi-domain few-shot classification (ICCV)

A multi-mode modulator for multi-domain few-shot classification (ICCV)

Yanbin Liu 8 Apr 28, 2022
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations

TopClus The source code used for Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations, published in WWW 2022. Requ

Yu Meng 63 Dec 18, 2022
The official repo of the CVPR2021 oral paper: Representative Batch Normalization with Feature Calibration

Representative Batch Normalization (RBN) with Feature Calibration The official implementation of the CVPR2021 oral paper: Representative Batch Normali

Open source projects of ShangHua-Gao 76 Nov 09, 2022
🔮 Execution time predictions for deep neural network training iterations across different GPUs.

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

Geoffrey Yu 44 Dec 27, 2022
An implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

Simon Niklaus 984 Dec 16, 2022
Cross-view Transformers for real-time Map-view Semantic Segmentation (CVPR 2022 Oral)

Cross View Transformers This repository contains the source code and data for our paper: Cross-view Transformers for real-time Map-view Semantic Segme

Brady Zhou 363 Dec 25, 2022
[SDM 2022] Towards Similarity-Aware Time-Series Classification

SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie

Daochen Zha 49 Dec 27, 2022
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.

Reinforcement-trading This project uses Reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can

Deepender Singla 1.4k Dec 22, 2022
Pytorch implementation of the DeepDream computer vision algorithm

deep-dream-in-pytorch Pytorch (https://github.com/pytorch/pytorch) implementation of the deep dream (https://en.wikipedia.org/wiki/DeepDream) computer

102 Dec 05, 2022
Benchmarking Pipeline for Prediction of Protein-Protein Interactions

B4PPI Benchmarking Pipeline for the Prediction of Protein-Protein Interactions How this benchmarking pipeline has been built, and how to use it, is de

Loïc Lannelongue 4 Jun 27, 2022
Picasso: A CUDA-based Library for Deep Learning over 3D Meshes

The Picasso Library is intended for complex real-world applications with large-scale surfaces, while it also performs impressively on the small-scale applications over synthetic shape manifolds. We h

97 Dec 01, 2022
Tom-the-AI - A compound artificial intelligence software for Linux systems.

Tom the AI (version 0.82) WARNING: This software is not yet ready to use, I'm still setting up the GitHub repository. Should be ready in a few days. T

2 Apr 28, 2022
Coded illumination for improved lensless imaging

CodedCam Coded Illumination for Improved Lensless Imaging Paper | Supplementary results | Data and Code are available. Coded illumination for improved

Computational Sensing and Information Processing Lab 1 Nov 29, 2021
The implementation of "Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Band Speech Enhancement"

SF-Net for fullband SE This is the repo of the manuscript "Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Ban

Guochen Yu 36 Dec 02, 2022