Bruno Gavranović

Category_Theory_Machine_Learning. List of papers studying machine learning through the lens of category theory

Category_Theory_Resources. List of resources for learning Category Theory

Compositional_Deep_Learning. Deep learning via category theory and functional programming

DNC. Implementation of the Differentiable Neural Computer in Tensorflow

autodiff. Rudimentary automatic differentiation framework

Lens_Resources. Theory and Applications of Lenses and Optics

TensorType. Framework for type-safe pure functional and non-cubical tensor processing, written in Idris 2

Improved_WGAN. Implementation of the "Improved Training of Wasserstein GANs" paper in TensorFlow

Agda_Category_Theory. Formalization of category theory in Agda

DependentOpticsIdris2. Idris

-Co-AlgebraCheatSheet. List of initial algebras and final coalgebras of functors

GAN_Lecture_Materials. Generative Adversarial Networks presentation and workshop materials

Idris_Category_Theory. Idris

LSTM. Playing around with various LSTM architectures and figuring out TensorFlow

synthetic_gradients. Implementation of the "Decoupled Neural Interfaces using Synthetic Gradients" paper in PyTorch

Dependently_Typed_Einsum. WIP

CycleGAN. Implementation of the CycleGAN paper with Wassersein distance and gradient penalty

Agda_CT_Bug. Agda

idris-ct. formally verified category theory library

the-gan-zoo. A list of all named GANs!

ml. Simple neural network in numpy