EQL
Equation Learner, a neural network approach to symbolic regression
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Download Latest Version (.zip)- cp-n-10k-1-2-test.dat.gz
- cp-n-10k-1-test.dat.gz
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- div-n-10k-1.dat.gz
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- f4-n-5k-1-test.dat.gz
- f0-3layer.pdf
- SahooLampertMartius2018:EQLDiv.pdf
- 1.best_state
- 1.extrapoltrainloss
- 1.L1
- 1.last_state
- 1.MSE
- 1.res
- 1.trainloss
- 1.validerror
- all.dat
- createtasksIS-base.py
- Readme.md
- 2.best_state
- 2.extrapoltrainloss
- 2.L1
- 2.last_state
- 2.MSE
- 2.res
- 2.testerrors
- 2.trainloss
- 2.validerror
- all.dat
- createjobs.py
- Readme.md
- __init__.py
- graph_div.py
- mlfg_final.py
- model_selection_val_sparsity.py
- noise.py
- utils.py
- __init__.py
- createjobs-f1.py
- createjobs.py
- Evaluation.ipynb
- example_parameter_scan_result.txt
- ICML-Datasets.ipynb
- Readme.md
- __init__.py
- graph.py
- graph_div.py
- graph_separate.py
- mlfg_final.py
- mlp.py
- model_selection_val_sparsity.py
- noise.py
- svr.py
- utils.py
- __init__.py
- createjobs-f1.py
- Evaluation.ipynb
- Readme.md
- .gitignore
- LICENSE
- README.md
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