sjchoi86 / Choicenet
Licence: mit
Implementation of ChoiceNet
Stars: ✭ 125
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ChoiceNet
TensorFlow Implementation of ChoiceNet on regression tasks.
Summarized result:
arxiv
Paper:Classification (MNIST) Result
name | Result |
---|---|
Outlier Rate: 25.0% | |
Outlier Rate: 45.0% | |
Outlier Rate: 47.5% |
name | Result |
---|---|
Outlier Rate: 50.0% | |
Outlier Rate: 90.0% | |
Outlier Rate: 95.0% |
name | Result |
---|---|
Outlier Rate: 25.0% | |
Outlier Rate: 45.0% | |
Outlier Rate: 47.5% |
Regression Result
name | Training Data | Multi-Layer Perceptron | Mixture Density Network | ChoiceNet |
---|---|---|---|---|
oRate: 0.0% | ||||
oRate: 10.0% | ||||
oRate: 30.0% | ||||
oRate: 50.0% | ||||
oRate: 60.0% | ||||
oRate: 70.0% |
name | Training Data | Multi-Layer Perceptron | Mixture Density Network | ChoiceNet |
---|---|---|---|---|
oRate: 0.0% | ||||
oRate: 10.0% | ||||
oRate: 30.0% | ||||
oRate: 50.0% | ||||
oRate: 60.0% | ||||
oRate: 70.0% |
name | Training Data | Multi-Layer Perceptron | Mixture Density Network | ChoiceNet |
---|---|---|---|---|
oRate: 0.0% | ||||
oRate: 10.0% | ||||
oRate: 30.0% | ||||
oRate: 50.0% | ||||
oRate: 60.0% | ||||
oRate: 70.0% |
HowTo?
- run code/main_reg_run.ipynb
- Properly modify followings based on the working environment:
nWorker = 16
maxGPU = 8
- (I was using 16 CPUs / 8 TESLA P40s / 96GB RAM.)
Requirements
- Python3
- TF 1.4>=
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