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17 search results found

Awesome Knowledge Distillation ⭐ 3,222

Awesome Knowledge Distillation

Awesome Knowledge Distillation ⭐ 2,182

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

Continual Learning ⭐ 1,190

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Vitpose ⭐ 950

The official repo for [NeurIPS'22] "ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation" and [Arxiv'22] "ViTPose+: Vision Transformer Foundation Model for Generic Body Pose Estimation"

irresponsible innovation. Try now at https://chat.dev/

Brain Inspired Replay ⭐ 169

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

Official code for our ECCV'22 paper "A Fast Knowledge Distillation Framework for Visual Recognition"

[ECCV 2022] R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis

基于 Tensorflow，仿 Scikit-Learn 设计的深度学习自然语言处理框架。支持 40 余种模型类，涵盖语言模型、文本分类、NER、MRC、知识蒸馏等各个领域

Supermix ⭐ 72

Pytorch implementation of CVPR2021 paper: SuperMix: Supervising the Mixing Data Augmentation

Adaptive Wavelets ⭐ 60

Adaptive, interpretable wavelets across domains (NeurIPS 2021)

Augmented Interpretable Models ⭐ 35

Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.

Knowledgefactor ⭐ 31

[ECCV2022] Factorizing Knowledge in Neural Networks

Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.

Simdistill ⭐ 20

The official repo for [AAAI 2024] "SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection""

Idn Tensorflow ⭐ 12

TensorFlow Implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)

[ACL 2023] Code for paper “Tailoring Instructions to Student’s Learning Levels Boosts Knowledge Distillation”(https://arxiv.org/abs/2305.09651)

Linkless Link Prediction ⭐ 7

[ICML 2023] Linkless Link Prediction via Relational Distillation

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