gdikov/bayesian-architecture-learning

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Python
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MIT License
Created almost 5 years ago
Updated over 2 years ago

gdikov/bayesian-architecture-learning

gdikov

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Implementation of "Bayesian Learning of Neural Network Architectures"

hypertunity

A toolset for black-box hyperparameter optimisation.

hybrid-stereo-matching

Framework for event- and frame-based stereo matching using SNNs and MRFs

Jupyter Notebook

adversarial-variational-bayes

A Keras/TensorFlow-based implementation of Adversarial Variational Bayes by L. Mescheder et al.

calibrated-adversarial-learning

Reproducing the toy example in "Calibrated Adversarial Refinement for Multimodal Semantic Segmentation" by Kassapis et al.

Jupyter Notebook

protein-function-prediction

stochastic-segmentation-networks

Tutorial reimplementation of Monteiro et al. (2020) on a toy problem.

Jupyter Notebook

MNIST-challenge

The MNIST dataset tackled by several machine learning models coded from scratch

gdikov.github.io

MiniML

Minimalistic implementations of several ML algorithms like NNs, SOMs, vector quantization and Hopfield nets

SpikingStereoMatching

SpiNNaker implementation of a spiking stereo matching neural network