This collection includes trained weights for the controlled argument generation models which were fine-tuned on Common-Crawl and Reddit-Comments dumps. For more information, please refer to the paper and the GitHub repository linked in the paper. DISCLAIMER: All weights provided as downloads may be used for research purposes only. The user acknowledges and agrees that the data is provided on an “as-is” basis and that the licensor makes no representations or warranties of any kind.1.
This repository provides model weights for analyses in main figures from "Evolution-inspired augment...
A computing device may receive a first set of training data for training an ANN to predict output da...
Jebbara S, Cimiano P. Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture. ...
This collection holds (1) the argument aspect detection corpus, (2) the data to reproduce the traini...
Trained network weights for the paper "Compositionally restricted attention-based network for materi...
Part 4: Neural Computing and Swarm IntelligenceInternational audienceData weighting is important for...
SIGLEAvailable from British Library Document Supply Centre-DSC:3292.8854(99/5) / BLDSC - British Lib...
Neural conversational models require substantial amounts of dialogue data for their parameter estima...
This repository provides model weights for analyses in main figures from "EvoAug: improving generali...
We show that an interesting class of feed-forward neural networks can be understood as quantitative ...
This paper appears in: Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 19...
This work studies the sensitivity of neural networks to weight perturbations, firstly corresponding ...
Argument(ation) mining (AM) is an area of research in Artificial Intelligence (AI) that aims to iden...
<p><b>a:</b> Weights learned from the MNIST dataset. Each square in the grid represents the incoming...
This research demonstrates a method of discriminating the numerical relationships of neural network ...
This repository provides model weights for analyses in main figures from "Evolution-inspired augment...
A computing device may receive a first set of training data for training an ANN to predict output da...
Jebbara S, Cimiano P. Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture. ...
This collection holds (1) the argument aspect detection corpus, (2) the data to reproduce the traini...
Trained network weights for the paper "Compositionally restricted attention-based network for materi...
Part 4: Neural Computing and Swarm IntelligenceInternational audienceData weighting is important for...
SIGLEAvailable from British Library Document Supply Centre-DSC:3292.8854(99/5) / BLDSC - British Lib...
Neural conversational models require substantial amounts of dialogue data for their parameter estima...
This repository provides model weights for analyses in main figures from "EvoAug: improving generali...
We show that an interesting class of feed-forward neural networks can be understood as quantitative ...
This paper appears in: Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 19...
This work studies the sensitivity of neural networks to weight perturbations, firstly corresponding ...
Argument(ation) mining (AM) is an area of research in Artificial Intelligence (AI) that aims to iden...
<p><b>a:</b> Weights learned from the MNIST dataset. Each square in the grid represents the incoming...
This research demonstrates a method of discriminating the numerical relationships of neural network ...
This repository provides model weights for analyses in main figures from "Evolution-inspired augment...
A computing device may receive a first set of training data for training an ANN to predict output da...
Jebbara S, Cimiano P. Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture. ...