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awesome-multi-objective-deep-learning

github.com/baijiong-lin/awesome-multi-objective-deep-learning ↗

A comprehensive list of gradient-based multi-objective optimization algorithms in deep learning.

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Related SurveyFinding a Single SolutionFinding a Finite Set of SolutionsFinding an Infinite Set of SolutionsResources

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Related Survey

Finding a Single Solution

PaperLoss Balancing Methods
PaperLoss Balancing Methods
PaperLoss Balancing Methods
PaperLoss Balancing Methods
PaperLoss Balancing Methods
PaperLoss Balancing Methods

Finding a Finite Set of Solutions

PaperMethods without Using Preference Vectors
PaperMethods Based on Preference Vectors
PaperMethods Based on Preference Vectors
PaperMethods Based on Preference Vectors
PaperMethods Based on Preference Vectors
PaperMethods Based on Preference Vectors

Finding an Infinite Set of Solutions

PaperHypernetwork-based Methods
PaperHypernetwork-based Methods
PaperHypernetwork-based Methods
PaperHypernetwork-based Methods
PaperHypernetwork-based Methods
PaperPreference-Conditioned Network-based Methods

Resources

PaperSoftware
PaperSoftware

Showing a sample of 66 resources. View the full list on GitHub →