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Knowledge Graph embedding in Python and Pytorch.

Project description

TorchKGE

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TorchKGE: Knowledge Graph embedding in Python and Pytorch.

History

0.10.0 (2019-07-19)

  • Implemented Triplet Classification evaluation method

  • Added Negative Sampler objects to standardize negative sampling methods.

0.9.0 (2019-07-17)

  • Implemented HolE model (Nickel et al.)

  • Implemented ComplEx model (Trouillon et al.)

  • Implemented ANALOGY model (Liu et al.)

  • Added knowledge graph splitting into train, validation and test instead of just train and test.

0.8.0 (2019-07-09)

  • Implemented Bernoulli negative sampling as in Wang et al. paper on TransH (2014).

0.7.0 (2019-07-01)

  • Implemented Mean Reciprocal Rank measure of performance.

  • Implemented Logistic Loss.

  • Changed implementation of margin loss to use torch methods.

0.6.0 (2019-06-25)

  • Implemented DistMult

0.5.0 (2019-06-24)

  • Changed implementation of LinkPrediction ranks by moving functions to model methods.

  • Implemented RESCAL.

0.4.0 (2019-05-15)

  • Fixed a major bug/problem in the Evaluation protocol of LinkPrediction.

0.3.1 (2019-05-10)

  • Minor bug fixes in the various normalization functions.

0.3.0 (2019-05-09)

  • Fixed CUDA support.

0.2.0 (2019-05-07)

  • Added support for filtered performance measures.

0.1.7 (2019-04-03)

  • First real release on PyPI.

0.1.0 (2019-04-01)

  • First release on PyPI.

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