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 | 634 | |
2021 | 412 | |
2020 | 202 | |
2016 | 181 | |
2019 | 128 | |
2016 | 123 | |
2020 | 108 | |
2021 | 100 | |
2018 | 95 | |
2021 | 52 | |
2020 | 46 | |
2020 | 28 | |
2020 | 25 | |
2016 | 14 | |
2021 | 13 | |
2020 | 10 | |
2018 | 9 | |
2021 | 9 | |
2020 | 8 | |
2019 | 7 | |
2021 | 6 | |
2019 | 5 | |
2020 | 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 |