104 Open source projects that are alternatives of or similar to Meta Learning Lstm Pytorch

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

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

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

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

MetaGenRL, a novel meta reinforcement learning algorithm. Unlike prior work, MetaGenRL can generalize to new environments that are entirely different from those used for meta-training.

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

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

A PyTorch Library for Meta-learning Research

Code for: "Learning To Adapt For Stereo" accepted at CVPR2019

Repository for few-shot learning machine learning projects

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..

Pytorch implementation of Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs (Interspeech, 2020)

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

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

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

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

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

No description or website provided.

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

Official repository of https://arxiv.org/abs/2111.04040v1

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

Repository containing code for the paper "Meta-Learning with Sparse Experience Replay for Lifelong Language Learning".

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

Meta-DETR: Official PyTorch Implementation

Automated Machine Learning with scikit-learn

Collection for Few-shot Learning

FSL-Mate: A collection of resources for few-shot learning (FSL).

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

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

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

Awesome Multitask Learning Resources

Tensorflow Implementation of MAML

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

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".

Meta graph convolutional neural network-assisted resilient swarm communications

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

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

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

Personalizing Dialogue Agents via Meta-Learning

Meta-Feature Extractor

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

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

Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

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

This repository implements the paper, Model-Agnostic Meta-Leanring for Fast Adaptation of Deep Networks.

Memory efficient MAML using gradient checkpointing

Source code for CVPR 2020 paper "Scene-Adaptive Video Frame Interpolation via Meta-Learning"

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

My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning

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

Code for meta-learning initializations for image segmentation

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.

This is an official implementation for "Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising"(KDD2021).

Meta learning with BERT as a learner

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

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

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

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

Graph meta learning via local subgraphs (NeurIPS 2020)

A dataset of datasets for learning to learn from few examples