Uncertainty Reduction for Model Adaptation in Semantic Segmentation S Prabhu Teja, F Fleuret Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 150* | 2021 |
Optimizer benchmarking needs to account for hyperparameter tuning PT Sivaprasad, F Mai, T Vogels, M Jaggi, F Fleuret International conference on machine learning, 9036-9045, 2020 | 56* | 2020 |
Test time adaptation through perturbation robustness PT Sivaprasad, F Fleuret arXiv preprint arXiv:2110.10232, 2021 | 25* | 2021 |
A ballistic stroke representation of online handwriting for recognition SP Teja, AM Namboodiri 2013 12th International Conference on Document Analysis and Recognition, 857-861, 2013 | 10 | 2013 |
Continual learning with low rank adaptation M Wistuba, PT Sivaprasad, L Balles, G Zappella arXiv preprint arXiv:2311.17601, 2023 | 6 | 2023 |
PAUMER: Patch Pausing Transformer for Semantic Segmentation E Courdier, PT Sivaprasad, F Fleuret arXiv preprint arXiv:2311.00586, 2023 | 2 | 2023 |
Choice of PEFT Technique in Continual Learning: Prompt Tuning is Not All You Need M Wistuba, PT Sivaprasad, L Balles, G Zappella arXiv preprint arXiv:2406.03216, 2024 | 1 | 2024 |
On the Choice of Learning Rate for Local SGD L Balles, PT Sivaprasad, C Archambeau Transactions on Machine Learning Research, 2023 | 1 | 2023 |
Confidence Matters: Applications to Semantic Segmentation PT Sivaprasad EPFL, 2023 | | 2023 |