130 Open source projects that are alternatives of or similar to FOCAL-ICLR

Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"

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

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)

6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"

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

The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"

Deep Recommenders

ProMP: Proximal Meta-Policy Search

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

My personal toolkit for PyTorch development.

Inspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.

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

Code for "One-Shot Visual Imitation Learning via Meta-Learning"

HyperFace

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

LibFewShot: A Comprehensive Library for Few-shot Learning.

A classified list of meta learning papers based on realm.

Multi-Task Learning package built with tensorflow 2 (Multi-Gate Mixture of Experts, Cross-Stitch, Ucertainty Weighting)

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

Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

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

A framework for large scale recommendation algorithms.

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

Local Fisher Discriminant Analysis in R

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

Source code (train/test) accompanying the paper entitled "Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach" in CVPR 2019 (https://arxiv.org/abs/1903.10764).

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

Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"

A deep learning framework for building multimodal multi-task learning systems.

Great resources for making Reinforcement Learning work in Real Life situations. Papers,projects and more.

TensorFlow 2.0 implementation of MAML.

Tools for generating mini-ImageNet dataset and processing batches

Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen, "Compacting, Picking and Growing for Unforgetting Continual Learning," Thirty-third Conference on Neural Information Processing Systems, NeurIPS 2019

Code for the paper "Evolved Policy Gradients"

Asymmetric Multi-Task Attention Network for Prostate Bed Segmentation in CT Images

Python module to interface with OpenML

Code release for Your “Flamingo” is My “Bird”: Fine-Grained, or Not (CVPR 2021 Oral)

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

Yi-Min Chou, Yi-Ming Chan, Jia-Hong Lee, Chih-Yi Chiu, Chu-Song Chen, "Unifying and Merging Well-trained Deep Neural Networks for Inference Stage," International Joint Conference on Artificial Intelligence (IJCAI), 2018

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

PCC Net: Perspective Crowd Counting via Spatial Convolutional Network

Jia-Hong Lee, Yi-Ming Chan, Ting-Yen Chen, and Chu-Song Chen, "Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications," IEEE International Conference on Multimedia Information Processing and Retrieval, MIPR 2018

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

A lightweight module for Multi-Task Learning in pytorch.

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

R package for Distance Metric Learning

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

A Pytorch implementation of DeepCrack and RoadNet projects.

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

Awesome Few-shot learning

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".

Multi-task learning smile detection, age and gender classification on GENKI4k, IMDB-Wiki dataset.

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

Multi-Task Deep Neural Networks for Natural Language Understanding

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

A prototype version of our submitted paper: Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives.

Learning To Compare For Text , Few shot learning in text classification

awesome few shot / meta learning papers

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem

Multi-task deep learning framework for multi-omics data analysis