149 Open source projects that are alternatives of or similar to Learning To Learn By Pytorch

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

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

Awesome Multitask Learning Resources

Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.

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

Gorgonia is a library that helps facilitate machine learning in Go.

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

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.

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

Implementing Multiple Layer Neural Network from Scratch

A single header-only C++ library for least squares fitting.

Meta-DETR: Official PyTorch Implementation

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..

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

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

No description or website provided.

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

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

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

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

The simplest form of an artificial neural network explained and demonstrated.

My workshop on machine learning using python language to implement different algorithms

Automated Machine Learning with scikit-learn

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Six snippets of code that made deep learning what it is today.

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

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

Collection for Few-shot Learning

Minimalistic Multiple Layer Neural Network from Scratch in Python.

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

Meta graph convolutional neural network-assisted resilient swarm communications

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

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

⭐️ Univariate Linear Regression with Gradient Descent in JavaScript (Vectorized)

Personalizing Dialogue Agents via Meta-Learning

OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions

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

Repository for few-shot learning machine learning projects

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

A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN

A PureScript, browser-based implementation of simple linear regression.

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

First-order optimization tools

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Toy implementations of some popular ML optimizers using Python/JAX

a lightweight C++17 library of numerical optimization methods for nonlinear functions (Including L-BFGS-B for TensorFlow)

Final Project of the Udacity AI Programming with Python Nanodegree

A PyTorch implementation of Learning to learn by gradient descent by gradient descent

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

Neural Networks in Java 8 with CuDNN and Aparapi

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.

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

Code for meta-learning initializations for image segmentation

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

Image morphing without reference points by applying warp maps and optimizing over them.

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

Meta-Feature Extractor

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

A dataset of datasets for learning to learn from few examples

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