[TPAMI'2024] Multi-sensor Learning Enables Information Transfer across Different Sensory Data and Augments Multi-modality Imaging
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Updated
Sep 24, 2024 - Python
[TPAMI'2024] Multi-sensor Learning Enables Information Transfer across Different Sensory Data and Augments Multi-modality Imaging
Implementation of NAACL 2024 main conference paper: Named Entity Recognition Under Domain Shift via Metric Learning for Life Science
[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.
[Paper][AAAI 2023] DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning
PyContinual (An Easy and Extendible Framework for Continual Learning)
An Extensible Continual Learning Framework Focused on Language Models (LMs)
The idea is to use pretrained deep learning algorithms such as mobilenet to predict objects in a image.
Code and pretrained models for paper: Data-Free Adversarial Distillation
Code for NeurIPS 2020 Paper --- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
[ECCV2022] Factorizing Knowledge in Neural Networks
Pytorch implementation of various Knowledge Distillation (KD) methods.
Code for ECML/PKDD 2020 Paper --- Continual Learning with Knowledge Transfer for Sentiment Classification
Multiple methods' implementations to transfer the knowledge between Neural Networks and save/plot/compare the results.
PyTorch implementation of (Hinton) Knowledge Distillation and a base class for simple implementation of other distillation methods.
Knowledge Transfer via Dense Cross-layer Mutual-distillation (ECCV'2020)
Official PyTorch implementation of "A Comprehensive Overhaul of Feature Distillation" (ICCV 2019)
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons (AAAI 2019)
Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"
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