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bert

TensorFlow code and pre-trained models for BERT

daily-reading

data-requests-query-dataset

Dataset of queries created with a crowdsourcing experiment. Data requests originated from https://data.gov.uk/dataset/data-requests-at-data-gov-uk

dilp-core

Python and TensorFlow implementation of the paper "Learning Explanatory Rules from Noisy Data." Evans Richard and Edward Grefenstette. Journal of Artificial Intelligence Research 61 (2018): 1-64.

drum

DRUM end to end differentiable rule mining on knowledge graphs

ecir2020-dataset-search

faithfulre

Data and codes for faithful rule extraction.

g-mpnn-r

grail

Inductive relation prediction by subgraph reasoning, ICML'20

graphqembed

Learning to query complex networks

hypergcn

NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs

kgtransformer

kgTransformer: pre-training for reasoning over complex KG queries (KDD 22)

lernd

Lernd is ∂ILP (dILP) framework implementation based on Deepmind's paper Learning Explanatory Rules from Noisy Data.

lerp

Official Repository for ICLR 2023 Paper: Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

neural-lp

Differentiable Learning of Logical Rules for Knowledge Base Reasoning

nju_kepractice

The final project for the Knowledge Engineering course at Nanjing University.

oxthesistemplate

LaTeX template for an Oxford University thesis

profiles-2019

red-gnn

Knowledge Graph Reasoning with Relational Digraph. WebConf 2022

sipser-computation-3rd-solutions

Solutions to all questions of the book Introduction to the Theory of Computation, 3rd edition by Michael Sipser

xiaxia-wang.github.io