YuheD / awesome-model-transferability-estimation

A collection of model transferability estimation methods.

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awesome-model-transferability-estimation

A collection of model transferability estimation methods.

This repo is still in progress.

Source-independent

2016

  • Learning to Select Pre-trained Deep Representations with Bayesian Evidence Framework [CVPR]

2019

  • Transferability and Hardness of Supervised Classification Tasks [ICCV]
  • An information theoretic approach to transferability in task transfer learning [ICIP] [Codes]
  • TASK2VEC: Task Embedding for Meta-Learning [ICCV]

2020

  • LEEP: A New Measure to Evaluate Transferability of Learned Representations [ICML] [Slides] [PyTorch]
  • Source Model Selection for Deep Learning in the Time Series Domain [IEEE Access]
  • Ranking and rejecting of pre-trained deep neural networks in transfer learning based on separation index [ArXiv]

2021

  • Ranking Neural Checkpoints [CVPR]
  • LogME: Practical Assessment of Pre-trained Models for Transfer Learning [ICML] [PyTorch]
  • Scalable Diverse Model Selection for Accessible Transfer Learning [NeurIPS] [PyTorch]
  • A linearized framework and a new benchmark for model selection for fine-tuning [ArXiv]

2022

  • Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance [ECML PKDD]
  • Frustratingly Easy Transferability Estimation [ICML] [Slides]
  • Transferability Estimation Using Bhattacharyya Class Separability [CVPR]
  • Transferability Metrics for Selecting Source Model Ensembles [CVPR]
  • How stable are Transferability Metrics evaluations? [ECCV] [TensorFlow]
  • Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning [NeurIPS] [Codes]
  • Pitfalls in Measuring Neural Transferability [NeurIPSW]
  • Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs [JMLR]
  • PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks [ECCV] [Codes]
  • Evidence > Intuition: Transferability Estimation for Encoder Selection [EMNLP]
  • Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space [ECCV]
  • Efficient Semantic Segmentation Backbone Evaluation for Unmanned Surface Vehicles based on Likelihood Distribution Estimation [MSN]
  • Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning [NeurIPS]

2023

  • Model Spider: Learning to Rank Pre-Trained Models Efficiently [Arxiv]
  • Towards Estimating Transferability using Hard Subsets [ArXiv]
  • Pick the Best Pre-trained Model: Towards Transferability Estimation for Medical Image Segmentation [MICCAI]
  • Transferability Metrics for Object Detection [ArXiv]
  • Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance[ArXiv]
  • ETran: Energy-Based Transferability Estimation [ICCV]
  • How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability [ICCV]
  • Exploring Model Transferability through the Lens of Potential Energy[ICCV]
  • Unleashing the power of Neural Collapse for Transferability Estimation [ArXiv]
  • Foundation Model is Efficient Multimodal Multitask Model Selector [ArXiv]
  • Towards Robust Multi-Modal Reasoning via Model Selection [ArXiv]
  • Graph-based fine-grained model selection for multi-source domain [PAA]
  • Guided Recommendation for Model Fine-Tuning [CVPR]
  • Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How [ArXiv]
  • Estimating the Transfer Learning Ability of a Deep Neural Networks by Means of Representations [NCMLCR]
  • Efficient Prediction of Model Transferability in Semantic Segmentation Tasks [ICIP]
  • The Performance of Transferability Metrics Does Not Translate to Medical Tasks [MICCAI workshop]
  • How to Determine the Most Powerful Pre-trained Language Model without Brute Force Fine-tuning? An Empirical Survey [ArXiv]
  • Guided recommendation for model fine-tuning [CVPR]

Source-dependent

2019

  • Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning [CVPR]
  • Model reuse with reduced kernel mean embedding specification [ArXiv]

2020

  • Duality diagram similarity: a generic framework for initialization selection in task transfer learning [ECCV]

2021

  • A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning NeurIPS
  • Transferability Estimation for Semantic Segmentation Task [ArXiv]
  • OTCE: A Transferability Metric for Cross-Domain Cross-Task Representations [CVPR] [Poster]
  • Practical Transferability Estimation for Image Classification Tasks [ArXiv]

2022

  • Transferability-Guided Cross-Domain Cross-Task Transfer Learning [ArXiv]
  • Transferability Estimation Based On Principal Gradient Expectation [ArXiv]

2023

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A collection of model transferability estimation methods.