julia-flowers
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An experiment in R to create flowers inspired in the Julia Set
RAT-SPN
Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
V0.2
- RAT-SPN model
- Experiments for generative learning of RAT-SPNs using EM
- Experiments for discriminative learning of RAT-SPNs using Adam
Setup
git clone https://github.com/cambridge-mlg/RAT-SPN
cd RAT-SPN
./install_tensorflow_venv.sh
source ratspn_venv/bin/activate
python download_preprocess_data.py
Quick Run for Generative Experiments
This will simply train a single RAT-SPN (no crossvalidation).
python quick_run_rat_spn_generative.py
python quick_eval_rat_spn_generative.py
Quick Run for Discriminative Training on MNIST
This will simply train a single RAT-SPN for each depth.
python quick_run_rat_spn_mnist.py
python quick_eval_rat_spn_discriminative.py
Full Training
See the run_.py and eval_.py files
Acknowledgments
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This project received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 797223 (HYBSPN).