Self-Supervised Learning

General • 46 methods

Self-Supervised Learning refers to a category of methods where we learn representations in a self-supervised way (i.e without labels). These methods generally involve a pretext task that is solved to learn a good representation and a loss function to learn with. Below you can find a continuously updating list of self-supervised methods.

Method Year Papers
2016 668
2021 439
2020 205
2016 182
2019 131
2016 123
2020 110
2021 108
2018 98
2021 54
2020 47
2020 28
2020 26
2016 14
2021 14
2021 10
2020 10
2018 9
2020 8
2019 7
2020 6
2021 6
2019 5
2019 4
2020 4
2018 4
2022 4
2022 4
2021 4
2020 3
2020 3
2020 3
2020 3
2017 2
2020 2
2021 2
2019 1
2019 1
2019 1
2019 1
2020 1
2021 1
2021 1
2022 1
2023 1