knowledge-transfer

Awesome Knowledge Distillation

Pytorch implementation of various Knowledge Distillation (KD) methods.

Official PyTorch implementation of "A Comprehensive Overhaul of Feature Distillation" (ICCV 2019)

Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons (AAAI 2019)

PyContinual (An Easy and Extendible Framework for Continual Learning)

Code and pretrained models for paper: Data-Free Adversarial Distillation

This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field

Knowledge Transfer via Dense Cross-layer Mutual-distillation (ECCV'2020)

Code for ECML/PKDD 2020 Paper --- Continual Learning with Knowledge Transfer for Sentiment Classification

Code for NeurIPS 2020 Paper --- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks

PyTorch implementation of (Hinton) Knowledge Distillation and a base class for simple implementation of other distillation methods.

Adaptive Model-based Transfer Evolutionary Algorithm

🥁 Teach a newbie how to perform better.

[ECCV2022] Factorizing Knowledge in Neural Networks

Multiple methods' implementations to transfer the knowledge between Neural Networks and save/plot/compare the results.

The Weizenbaum Institut „Knowledge Tool“ supports interdisciplinary debates by providing a workshop methodology based on predefined instructions and prefabricated workshop materials with the aim to structure and record multi-perspective exploration and analysis.

Learning in Growing Robots: Knowledge Transfer from Tadpole to Frog Robot

Source code for KTP project on networks in project management.

🧠 A DNN that uses knowledge transfer to perform localization and an RNN that studies and generates texts, built for a university Deep Learning course

This contains all of the experience of JET as a programmer from beginner to advance.

"Knowledge transfer in StackOverflow", a CSS seminar project by TUM students

The idea is to use pretrained deep learning algorithms such as mobilenet to predict objects in a image.

Promote documentation best practices