Awesome Knowledge Distillation
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Updated
May 23, 2024
Awesome Knowledge Distillation
Pytorch implementation of various Knowledge Distillation (KD) methods.
Official PyTorch implementation of "A Comprehensive Overhaul of Feature Distillation" (ICCV 2019)
PyContinual (An Easy and Extendible Framework for Continual Learning)
Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"
Code and pretrained models for paper: Data-Free Adversarial Distillation
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons (AAAI 2019)
An Extensible Continual Learning Framework Focused on Language Models (LMs)
This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field
PyTorch implementation of (Hinton) Knowledge Distillation and a base class for simple implementation of other distillation methods.
Code for ECML/PKDD 2020 Paper --- Continual Learning with Knowledge Transfer for Sentiment Classification
[Paper][AAAI 2023] DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning
Adaptive Model-based Transfer Evolutionary Algorithm
[ECCV2022] Factorizing Knowledge in Neural Networks
Code for NeurIPS 2020 Paper --- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
Knowledge Transfer via Dense Cross-layer Mutual-distillation (ECCV'2020)
🥁 Teach a newbie how to perform better.
[NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framework with diffusion model on graphs.
Repositorio del TFG Urban Street Mapping Transfer
Bonan & Samo. January 2023. Paper on cross-linguistic bias in health-related content in Transformer-based language models.
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