To run phi learning on linear gaussian (Fig1a)
python linear_gaussian_phi_learning.py
To run phi and theta learning on linear gaussian (Fig1b)
python linear_gaussian_model_learning.py
To run CTRNN experiment
python CTRNN_run_with_hydra.py
To run sequential VAE experiment
python dmlab.py
- pytorch
- hydra (for hyperparameter config) https://github.com/facebookresearch/hydra
- scipy
- tqdm
Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu
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BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation Installing The Dependencies $ conda create --name beametrics python
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TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.
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This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
Status: Archive (code is provided as-is, no updates expected) Grade School Math [Blog Post] [Paper] State-of-the-art language models can match human p
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