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1. floodGatesUp-DeePCfloodGatesUp-DeePCPublic

   This code can be used to reproduce the results in our paper ``Floodgates up to contain the DeePC and limit extrapolation''.

   Jupyter Notebook

2. data-conforming-controldata-conforming-controlPublic

   This code can be used to reproduce the results in our paper ``Data-conforming data-driven control: avoiding premature generalizations beyond data''

   Jupyter Notebook

3. linearizing-uncertainty-for-controllinearizing-uncertainty-for-controlPublic

   This code can be used to reproduce the results in our paper ``Extended Kalman filter---Koopman operator for tractable stochastic optimal control'.

   Julia 7 1

4. Active-Learning-Reinforcement-LearningActive-Learning-Reinforcement-LearningPublic

   This code can be used to reproduce the results in our paper ``Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach''.

   Jupyter Notebook 5

5. Policy-Iteration-Markov-Decision-Process-OOPPolicy-Iteration-Markov-Decision-Process-OOPPublic

   Policy iteration algorithm applied on finite state and action spaces Markov decision process.

   C++

6. Extended-Kalman-Filter-UsingPyTorchAutoGradExtended-Kalman-Filter-UsingPyTorchAutoGradPublic

   Uses PyTorch tensors and autograd | The extended Kalman filtering algorithm as a class: mean and covariance are attributes and propagation in time are methods | PyTorch autograd is used to return t…

   Python 3