TuckER: Tensor Factorization for Knowledge Graph Completion
TuckER
TuckER: Tensor Factorization for Knowledge Graph Completion
This codebase contains PyTorch implementation of the paper:
TuckER: Tensor Factorization for Knowledge Graph Completion.
Ivana Balažević, Carl Allen, and Timothy M. Hospedales.
Empirical Methods in Natural Language Processing (EMNLP), 2019.
[Paper]
TuckER: Tensor Factorization for Knowledge Graph Completion.
Ivana Balažević, Carl Allen, and Timothy M. Hospedales.
ICML Adaptive & Multitask Learning Workshop, 2019.
[Short Paper]
Link Prediction Results
Running a model
To run the model, execute the following command:
CUDA_VISIBLE_DEVICES=0 python main.py --dataset FB15k-237 --num_iterations 500 --batch_size 128
--lr 0.0005 --dr 1.0 --edim 200 --rdim 200 --input_dropout 0.3
--hidden_dropout1 0.4 --hidden_dropout2 0.5 --label_smoothing 0.1
Available datasets are:
FB15k-237
WN18RR
FB15k
WN18
To reproduce the results from the paper, use the