104 Open source projects that are alternatives of or similar to Crossdomainfewshot

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

Meta-Feature Extractor

DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020

Paper Lists, Notes and Slides, Focus on NLP. For summarization, please refer to https://github.com/xcfcode/Summarization-Papers

[CVPR'17] Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to high performance at fast speed..

Learning Meta Face Recognition in Unseen Domains, CVPR, Oral, 2020

Implementation of "Make One-Shot Video Object Segmentation Efficient Again” and the semi-supervised fine-tuning "e-OSVOS" approach (NeurIPS 2020).

Meta learning with BERT as a learner

Few-shot binary text classification with Induction Networks and Word2Vec weights initialization

Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms

The source codes of the paper "Improving Few-shot Text Classification via Pretrained Language Representations" and "When Low Resource NLP Meets Unsupervised Language Model: Meta-pretraining Then Meta-learning for Few-shot Text Classification".

A resource list for causality in statistics, data science and physics

Learning to Learn how to Learn: Self-Adaptive Visual Navigation using Meta-Learning (https://arxiv.org/abs/1812.00971)

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.

Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".

Collection for Few-shot Learning

Meta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)

Awesome Multitask Learning Resources

Memory efficient MAML using gradient checkpointing

Meta graph convolutional neural network-assisted resilient swarm communications

pytorch implementation of Optimization as a Model for Few-shot Learning

Personalizing Dialogue Agents via Meta-Learning

Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning

"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.

Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"

All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

A modular toolbox for meta-learning research with a focus on speed and reproducibility.

Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)

ProMP: Proximal Meta-Policy Search

Repository for few-shot learning machine learning projects

The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].

Automated Machine Learning with scikit-learn

The code for paper "CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning"

A dataset of datasets for learning to learn from few examples

[ICLR'19] Meta-learning with differentiable closed-form solvers

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..

A classified list of meta learning papers based on realm.

Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)

A PyTorch Library for Meta-learning Research

This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset

My personal toolkit for PyTorch development.

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

Meta Self-learning for Multi-Source Domain Adaptation： A Benchmark

A list of recent papers about Meta / few-shot learning methods applied in NLP areas.

[IJCAI 2021] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

Graph meta learning via local subgraphs (NeurIPS 2020)

No description or website provided.

Meta R-CNN : Towards General Solver for Instance-level Low-shot Learning

Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"

Python module to interface with OpenML

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).

PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models (IN PROGRESS)

Tensorflow Implementation of MAML