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maximally_interfered_retrieval

Codebase for "Online Continual Learning with Maximally Interfered Retrieval"

mdd

Code released for ICML 2019 paper "Bridging Theory and Algorithm for Domain Adaptation".

mega

[NeurIPS 2020, Spotlight] Improved Schemes for Episodic Memory-based Lifelong Learning

mer

Fork of the GEM project (https://github.com/facebookresearch/GradientEpisodicMemory) including Meta-Experience Replay (MER) methods from the ICLR 2019 paper (https://openreview.net/pdf?id=B1gTShAct7)

mirflickr_features

Visual features extracted from the MIR-Flickr images dataset.

mldg

The demo code for the MLDG paper "Learning to Generalize: Meta-Learning for Domain Generalization", https://arxiv.org/abs/1710.03463, https://arxiv.org/pdf/1710.03463.pdf

nlp_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

online-continual-learning

A collection of online continual learning paper implementations for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and a survey under review.

osaka

Codebase for "Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning"

patchvisiontransformer

pdfdiff

Command-line tool to inspect the difference between (the text in) two PDF files

perceiver-pytorch

Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch

perceiver_mnist

Just a quick toy example of the Perceiver architecture (PyTorch & PyTorch Lightning)

prototypical-networks-for-few-shot-learning-pytorch

Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch

prs

Official Repository for our ECCV2020 paper: Imbalanced Continual Learning with Partitioning Reservoir Sampling

pytorch-leo

Pytorch Implemtation of Meta-Learning with Latent Embedding Optimization

pytorch-metric-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

qcloud-documents

腾讯云官方文档

race

Implementation of Random Compression Method for Online Multi-label Streams

rainbow-is-all-you-need

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

regression-losses-pytorch

Experimenting with different regression losses. Implemented in Pytorch.

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

repdistiller

[ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods

rethinking_er

Code to reproduce the experiments of "Rethinking Experience Replay: a Bag of Tricks for Continual Learning"

rpsnet

Official Implementation of "Random Path Selection for Incremental Learning" paper. NeurIPS 2019

saml

Collect and Select: Semantic Alignment Metric Learning for Few-shot Learning

sdc-il

Semantic Drift Compensation for Class-Incremental Learning (CVPR2020)

shap

A game theoretic approach to explain the output of any machine learning model.

sluice-networks

Code for Sluice networks: Learning what to share between loosely related tasks

streaming-label-learning-

Streaming label learning with label on the fly