#
meta-learning
Here are 169 public repositories matching this topic...
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
-
Updated
Nov 26, 2018
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
-
Updated
Jun 16, 2020 - Python
Open
Add more tutorials
seba-1511
commented
Mar 3, 2020
As suggested on Reddit, it would be nice to have more tutorials.
A simple idea is to base them on our existing examples. The tutorial could explain how each implemented method works
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
-
Updated
Oct 22, 2019 - Python
A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
tensorflow
pytorch
hyperparameter-optimization
awesome-list
quantization
nas
automl
model-compression
neural-architecture-search
meta-learning
architecture-search
quantized-training
model-acceleration
automated-feature-engineering
quantized-neural-network
-
Updated
Apr 16, 2020
Repository for few-shot learning machine learning projects
-
Updated
Nov 25, 2019 - Python
[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..
machine-learning
computer-vision
deep-learning
object-tracking
meta-learning
cvpr2017
correlation-filter
-
Updated
May 31, 2018 - MATLAB
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
machine-learning
tutorial
reinforcement-learning
deep-reinforcement-learning
q-learning
pomdps
policy-gradient
sarsa
a3c
dynamic-programming
imitation-learning
dyna
td-learning
actor-critic
meta-learning
-
Updated
Jan 22, 2019 - Jupyter Notebook
Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)
image-classification
convex-optimization
meta-learning
few-shot
metalearning
few-shot-learning
few-shot-recognition
cvpr2019
-
Updated
Nov 9, 2019 - Python
TensorFlow and PyTorch implementations of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)
-
Updated
May 14, 2020 - Python
A dataset of datasets for learning to learn from few examples
-
Updated
May 19, 2020 - Python
Collection for Few-shot Learning
-
Updated
Jun 13, 2020 - TeX
Awesome Multitask Learning Resources
machine-learning
deep-learning
transfer-learning
convex-optimization
domain-adaptation
multi-task-learning
meta-learning
federated-learning
few-shot-learning
sparse-learning
-
Updated
Apr 22, 2020
Code for "One-Shot Visual Imitation Learning via Meta-Learning"
-
Updated
Oct 8, 2018 - Python
This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset
-
Updated
Oct 19, 2017 - Python
Code for the paper "Evolved Policy Gradients"
machine-learning
reinforcement-learning
paper
evolutionary-strategy
continuous-control
meta-learning
-
Updated
Nov 22, 2018 - Python
joaquinvanschoren
commented
Feb 15, 2020
Description
The API Docs: http://openml.github.io/openml-python/master/api.html
do not cover the API config options, such as 'server, api_key, verbosity,...'
Could this be added?
Steps/Code to Reproduce
Try to look up the OpenML-Python config options on
http://openml.github.io/openml-python/master/api.html
Expected Results
Maybe a section 'Configuration' next to 'Top
Tools for generating mini-ImageNet dataset and processing batches
dataset
imagenet
one-shot-learning
meta-learning
miniimagenet
few-shot
few-shot-learning
mini-imagenet
-
Updated
May 23, 2020 - Python
A classified list of meta learning papers based on realm.
-
Updated
Jun 5, 2020
My personal toolkit for PyTorch development.
-
Updated
Aug 19, 2017 - Python
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)
-
Updated
Apr 12, 2020 - Python
Learning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)
-
Updated
Oct 22, 2019 - Python
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
-
Updated
May 20, 2020 - Python
Meta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)
-
Updated
May 13, 2020 - Python
pytorch implementation of Optimization as a Model for Few-shot Learning
-
Updated
Feb 26, 2019 - Python
The code for paper "CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning"
-
Updated
Jun 6, 2020 - Python
code for ICCV19 paper "Deep Meta Metric Learning"
pytorch
baseline
metric-learning
person-reidentification
resnet-50
meta-learning
vehicle-reidentification
-
Updated
Jul 30, 2019 - Python
[ICLR'19] Meta-learning with differentiable closed-form solvers
machine-learning
computer-vision
deep-learning
pytorch
classification
meta-learning
few-shot-learning
iclr2019
-
Updated
Dec 3, 2019 - Python
Improve this page
Add a description, image, and links to the meta-learning topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the meta-learning topic, visit your repo's landing page and select "manage topics."
i want to know whether autosklearn support multilabel task, thank you!