m-hahn/GOTU

Implementation for "Generalization on the Unseen, Logic Reasoning and Degree Curriculum"

This is an implementation for "Generalization on the Unseen, Logic Reasoning and Degree Curriculum" in the PyTorch framework.

Contents:

• token_transformer.py contains the code of the Transformer model used in the experiments.
• models.py contains the code for the rest of the models including MLP, mean-field, and random feaures model.
• utilities.py includes some helper functions for the main file, e.g., computation of Fourier coefficients.
• main.py is the main file for the experiments.
• examples.py contains the definitions of the tasks used in the paper.
• script.sh includes the commands for generating the results presented in the paper. Note that the hyperparameters used for different tasks/models is also included in this file.