Deep Learning for Computer Vision 2018 Spring
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Updated
Jul 3, 2018 - Python
Deep Learning for Computer Vision 2018 Spring
This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)
Lowshot learning with Tensorflow
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Zero-Shot Learning part)
Few-shot classification in Named Entity Recognition Task
Codes for low-shot-shrink-hallucinate paper imported from official repository and with added helper functions
Meta-learning by applying MAML to an inner variational auto-encoder to automatically learn generative models with few examples
Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"
Few-Shot Relation Extraction with AllenNLP
Matching Networks for one-shot learning in tensorflow (NIPS'16)
Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
Code containing implementation of prototypical networks paper with a few tweaks
Implementation of Matching Networks for One Shot Learning in TensorFlow 2.0
Cluttered Omniglot dataset and models
General Adversial Networks using Few shot learning
ACL 2019 paper:Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
An unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.
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