Vanessa Vichi
|
4c2bfb1af9
|
Jupyter notebook used for 1) training the NN, 2) evaluating its performance on the NEOPOP test set and on the real NEOs dataset
|
2 years ago |
|
Vanessa Vichi
|
9d4c656139
|
DataFrames with the attributable elements
|
2 years ago |
|
Vanessa Vichi
|
35a0e891fd
|
Pre-processed NEOs DataFrame
|
2 years ago |
|
Vanessa Vichi
|
fb3ba5006d
|
Saved weights of Models 1,2 after a 500-epoch training (for both models) and a 1000-epoch training for Model 1
|
2 years ago |
Vanessa Vichi
|
2077014614
|
Conversion from Keplerian elements to attributable elements
|
2 years ago |
|
Vanessa Vichi
|
66775f772a
|
Jupyter Notebook for pre-processing of the NEOs DataFrame
|
2 years ago |
|
Vanessa Vichi
|
dc610efe37
|
Jupyter notebook for choosing the best initialization technique
|
2 years ago |
|
Vanessa Vichi
|
b3196ff82b
|
Jupyter notebook for evaluating the baseline performance: comparison of various metrics for the baseline model, the linear regression model and the polynomial regression model of degrees 2 and 3
|
2 years ago |
|
Vanessa Vichi
|
fea26621fc
|
Jupyter notebook for splitting the NEOPOP dataset into training, validation and test (with checks over the distribution of the various parts)
|
2 years ago |
|
Vanessa Vichi
|
67bbd480a4
|
Jupyter notebook for preliminary data exploration
|
2 years ago |
|
Vanessa Vichi
|
66021848e3
|
NEOPOP DataFrame split into training, validation, test
|
2 years ago |
|
Vanessa Vichi
|
44da7616fa
|
Output files of the NEOPOP run
|
2 years ago |
Vanessa Vichi
|
598f8fedd3
|
NEOs DataFrame
|
2 years ago |
|
Vanessa Vichi
|
81b4e797b3
|
NEOPOP DataFrame
|
2 years ago |
 v.vichi3
|
a491844d25
|
Initial commit
|
2 years ago |