Automated Theorem Proving on HolStep (Conditional)

Metric: Classification Accuracy (higher is better)

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#	Model↕	Classification Accuracy▼	Extra Data	Paper	Date↕	Code
1	MPNN-DagLSTM	0.916	No	Improving Graph Neural Network Representations o...	2019-11-15	Code
2	FormulaNet	0.903	No	Premise Selection for Theorem Proving by Deep Gr...	2017-09-28	Code
3	FormulaNet-basic	0.891	No	Premise Selection for Theorem Proving by Deep Gr...	2017-09-28	Code
4	Siamese 1D CNN-LSTM	0.83	No	HolStep: A Machine Learning Dataset for Higher-o...	2017-03-01	Code
5	Siamese 1D CNN	0.82	No	HolStep: A Machine Learning Dataset for Higher-o...	2017-03-01	Code

#1MPNN-DagLSTMSOTA
0.916
Classification Accuracy· 2019-11-15
Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling Code
#2FormulaNetSOTA
0.903
Classification Accuracy· 2017-09-28
Premise Selection for Theorem Proving by Deep Graph Embedding Code
#3FormulaNet-basic
0.891
Classification Accuracy· 2017-09-28
Premise Selection for Theorem Proving by Deep Graph Embedding Code
#4Siamese 1D CNN-LSTMSOTA
0.83
Classification Accuracy· 2017-03-01
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving Code
#5Siamese 1D CNN
0.82
Classification Accuracy· 2017-03-01
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving Code