Probabilistic programming stuff 2
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Updated
Jul 30, 2020 - Python
Probabilistic programming stuff 2
The collection of raw and generated (with transformations) images from the original Omniglot Dataset.
This is pedagogical implementation of MAML Algorithm.
Reimplementation of "VAE with a VampPrior" by Jakub M. Tomczak et al., as part of the DD2434 Machine Learning, Advanced Course at KTH
Memory Augmented Neural Networks, a Black-Box Meta-Learner that uses an LSTMs for few-shot classification
Implementation of "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Implementation of Few-shot Binary Image Classification using Contrastive Learning-based Approach in PyTorch
Prototypical Networks for the task of few-shot image classification on Omniglot and mini-ImageNet.
Implementation of Variational Memory Addressing for generative few-shot learning in PyTorch
This repository implements the paper, Model-Agnostic Meta-Leanring for Fast Adaptation of Deep Networks.
Example of one shot learning and few shot learning with omniglot dataset.
Implementation of Matching Networks for One Shot Learning in TensorFlow 2.0
a deep recurrent model for exchangeable data
Implementation of Siamese-Networks for One Shot Learning in TensorFlow 2.0
Cluttered Omniglot dataset and models
Implementation of Prototypical Networks for Few-shot Learning in TensorFlow 2.0
Multi-task learning for image classification implemented in PyTorch.
This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset
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