learning/annotated_deep_learning_paper_implementations
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docs/index.html
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@ -110,6 +110,11 @@ implementations.</p>
<li><a href="gan/stylegan/index.html">StyleGAN 2</a></li> <li><a href="gan/stylegan/index.html">StyleGAN 2</a></li>
</ul> </ul>
<h4>✨ <a href="sketch_rnn/index.html">Sketch RNN</a></h4> <h4>✨ <a href="sketch_rnn/index.html">Sketch RNN</a></h4>
<h4>✨ <a href="cfr/index.html">Counterfactual Regret Minimization (CFR)</a></h4>
<p>Solving games with incomplete information such as poker with CFR.</p>
<ul>
<li><a href="cfr/kuhn/index.html">Kuhn Poker</a></li>
</ul>
<h4>✨ <a href="rl/index.html">Reinforcement Learning</a></h4> <h4>✨ <a href="rl/index.html">Reinforcement Learning</a></h4>
<ul> <ul>
<li><a href="rl/ppo/index.html">Proximal Policy Optimization</a> with <li><a href="rl/ppo/index.html">Proximal Policy Optimization</a> with

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labml_nn/__init__.py
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@ -50,6 +50,12 @@ implementations.
#### ✨ [Sketch RNN](sketch_rnn/index.html) #### ✨ [Sketch RNN](sketch_rnn/index.html)
#### ✨ [Counterfactual Regret Minimization (CFR)](cfr/index.html)
Solving games with incomplete information such as poker with CFR.
* [Kuhn Poker](cfr/kuhn/index.html)
#### ✨ [Reinforcement Learning](rl/index.html) #### ✨ [Reinforcement Learning](rl/index.html)
* [Proximal Policy Optimization](rl/ppo/index.html) with * [Proximal Policy Optimization](rl/ppo/index.html) with
[Generalized Advantage Estimation](rl/ppo/gae.html) [Generalized Advantage Estimation](rl/ppo/gae.html)

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readme.md
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@ -56,6 +56,12 @@ implementations almost weekly.
#### ✨ [Sketch RNN](https://nn.labml.ai/sketch_rnn/index.html) #### ✨ [Sketch RNN](https://nn.labml.ai/sketch_rnn/index.html)
#### ✨ [Counterfactual Regret Minimization (CFR)](https://nn.labml.ai/cfr/index.html)
Solving games with incomplete information such as poker with CFR.
* [Kuhn Poker](https://nn.labml.ai/cfr/kuhn/index.html)
#### ✨ [Reinforcement Learning](https://nn.labml.ai/rl/index.html) #### ✨ [Reinforcement Learning](https://nn.labml.ai/rl/index.html)
* [Proximal Policy Optimization](https://nn.labml.ai/rl/ppo/index.html) with * [Proximal Policy Optimization](https://nn.labml.ai/rl/ppo/index.html) with
[Generalized Advantage Estimation](https://nn.labml.ai/rl/ppo/gae.html) [Generalized Advantage Estimation](https://nn.labml.ai/rl/ppo/gae.html)