First Neural Conjecturing Datasets and Experiments

29 May 2020 Josef Urban Jan Jakubův

We describe several datasets and first experiments with creating conjectures by neural methods. The datasets are based on the Mizar Mathematical Library processed in several forms and the problems extracted from it by the MPTP system and proved by the E prover using the ENIGMA guidance... (read more)

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Methods used in the Paper


METHOD TYPE
Cosine Annealing
Learning Rate Schedules
Weight Decay
Regularization
GELU
Activation Functions
Attention Dropout
Regularization
Linear Warmup With Cosine Annealing
Learning Rate Schedules
Discriminative Fine-Tuning
Fine-Tuning
Residual Connection
Skip Connections
Multi-Head Attention
Attention Modules
GPT-2
Transformers
Adam
Stochastic Optimization
ReLU
Activation Functions
Dropout
Regularization
BPE
Subword Segmentation
Dense Connections
Feedforward Networks
Layer Normalization
Normalization
Softmax
Output Functions
Scaled Dot-Product Attention
Attention Mechanisms