Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Related tags

Deep LearningKGs_and_Effect_Prediction_2020
Overview

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020.

Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

A snapshot of TERA (the Toxicological Effect and Risk Assessment Knowledge Graph) is avalible as a Zenodo dataset: DOI

To run the codes you must install KGE-Keras.

To reproduce results from paper run:

bash run.sh

This will take several days, depending on hardware avalible. 3-5 days on Nvidia GTX 1070ti. Set --MAX_TRIALS 0 to use default parameters.

Alternativly, unzip results.zip and run

python3 analyse_results.py

Related publications

  • Erik B. Myklebust, Ernesto Jimenez Ruiz, Jiaoyan Chen, Raoul Wolf, Knut Erik Tollefsen. Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings. Accepted for publication in the Semantic Web Journal, 2021. Paper REPOSITORY
Owner
Knowledge Graphs at the Norwegian Institute for Water Research
Knowledge Graphs at the Norwegian Institute for Water Research
GitHub Repository
Workshop Materials Delivered on 28/02/2022

intro-to-cnn-p1 Repo for hosting workshop materials delivered on 28/02/2022 Questions you will answer in this workshop Learning Objectives What are co

Beginners Machine Learning 5 Feb 28, 2022
PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021

Temporal Output Discrepancy for Active Learning PyTorch implementation of Semi-Supervised Active Learning with Temporal Output Discrepancy, ICCV 2021.

Siyu Huang 33 Dec 06, 2022
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator

DRL-robot-navigation Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gra

87 Jan 07, 2023
Towards Debiasing NLU Models from Unknown Biases

Towards Debiasing NLU Models from Unknown Biases Abstract: NLU models often exploit biased features to achieve high dataset-specific performance witho

Ubiquitous Knowledge Processing Lab 22 Jun 14, 2022
Airborne Optical Sectioning (AOS) is a wide synthetic-aperture imaging technique

AOS: Airborne Optical Sectioning Airborne Optical Sectioning (AOS) is a wide synthetic-aperture imaging technique that employs manned or unmanned airc

JKU Linz, Institute of Computer Graphics 39 Dec 09, 2022
LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura

4 Oct 05, 2022
Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Clara Meister 50 Nov 12, 2022
DeLighT: Very Deep and Light-Weight Transformers

DeLighT: Very Deep and Light-weight Transformers This repository contains the source code of our work on building efficient sequence models: DeFINE (I

Sachin Mehta 440 Dec 18, 2022
VGGVox models for Speaker Identification and Verification trained on the VoxCeleb (1 & 2) datasets

VGGVox models for speaker identification and verification This directory contains code to import and evaluate the speaker identification and verificat

338 Dec 27, 2022
To model the probability of a soccer coach leave his/her team during Campeonato Brasileiro for 10 chosen teams and considering years 2018, 2019 and 2020.

To model the probability of a soccer coach leave his/her team during Campeonato Brasileiro for 10 chosen teams and considering years 2018, 2019 and 2020.

Larissa Sayuri Futino Castro dos Santos 1 Jan 20, 2022
Async API for controlling Hue Lights

Hue API Async API for controlling Hue Lights Documentation: hue-api.nirantak.com Source: github.com/nirantak/hue-api Installation This is an async cli

Nirantak Raghav 4 Nov 16, 2022
Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN

Face Identity Disentanglement via Latent Space Mapping - Implement in pytorch with StyleGAN 2 Description Pytorch implementation of the paper Face Ide

Daniel Roich 58 Dec 24, 2022
DyNet: The Dynamic Neural Network Toolkit

The Dynamic Neural Network Toolkit General Installation C++ Python Getting Started Citing Releases and Contributing General DyNet is a neural network

Chris Dyer's lab @ LTI/CMU 3.3k Jan 06, 2023
Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper

AnimeGAN - Deep Convolutional Generative Adverserial Network PyTorch implementation of DCGAN introduced in the paper: Unsupervised Representation Lear

Rohit Kukreja 23 Jul 21, 2022
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution This is the official implementation code of the paper "CondLaneNe

Alibaba Cloud 311 Dec 30, 2022
PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/temporal/spatiotemporal databases

Introduction PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/tempor

RAGE UDAY KIRAN 43 Jan 08, 2023
Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs, ICCV 2021

Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs, ICCV 2021 Global Pooling, More than Meets the Eye: Posi

Md Amirul Islam 32 Apr 24, 2022
CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View

Rethinking Semantic Segmentation: A Prototype View Rethinking Semantic Segmentation: A Prototype View, Tianfei Zhou, Wenguan Wang, Ender Konukoglu and

Tianfei Zhou 239 Dec 26, 2022
WiFi-based Multi-task Sensing

WiFi-based Multi-task Sensing Introduction WiFi-based sensing has aroused immense attention as numerous studies have made significant advances over re

zhangx289 6 Nov 24, 2022
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes

Gradient Institute 127 Dec 12, 2022