| Convolutional neural fabrics S Saxena, J Verbeek NIPS16, 2016 | 261 | 2016 |
| Heterogeneous face recognition with CNNs S Saxena, J Verbeek ECCV16, 2016 | 137 | 2016 |
| Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum S Saxena, O Tuzel, D DeCoste NeurIPS19, 2019 | 81 | 2019 |
| Learning soft labels via meta learning N Vyas, S Saxena, T Voice arXiv preprint arXiv:2009.09496, 2020 | 27 | 2020 |
| Learning Unsupervised Visual Grounding Through Semantic Self-Supervision SA Javed, S Saxena, V Gandhi IJCAI 2019, NeurIPS ViGIL 2018 Workshop, 2018 | 27 | 2018 |
| Coordinated local metric learning S Saxena, J Verbeek Proceedings of the IEEE International Conference on Computer Vision …, 2015 | 19 | 2015 |
| SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models V Thangarasa, A Gupta, W Marshall, T Li, K Leong, D DeCoste, S Lie, ... ICLR Sparsity in Neural Networks Workshop, 2023 | 15 | 2023 |
| Dynamic curriculum learning via data parameters for noise robust keyword spotting T Higuchi, S Saxena, M Souden, TD Tran, M Delfarah, C Dhir ICASSP, 2021 | 7 | 2021 |
| Sparse Iso-FLOP Transformations for Maximizing Training Efficiency S Saxena, V Thangarasa, A Gupta, S Lie ICML 2024, 2023 | 4* | 2023 |
| Instance-Level Task Parameters: A Robust Multi-task Weighting Framework PKA Vasu, S Saxena, O Tuzel Proceedings of the IEEE International Conference on Computer Vision …, 2021 | 4 | 2021 |
| Object detection with position, pose, and shape estimation S Saxena, CO Tuzel, PKA Vasu US Patent 11,282,180, 2022 | 2 | 2022 |
| Key point recognition with uncertainty measurement S Saxena, W Wang, G Wu, N Srivastava, D Kottas, CO Tuzel, L Spinello, ... US Patent 11,080,562, 2021 | 1 | 2021 |
| Training with data dependent dynamic learning rates S Saxena, N Vyas, D DeCoste arXiv preprint arXiv:2105.13464, 2021 | 1 | 2021 |
| MediSwift: Efficient Sparse Pre-trained Biomedical Language Models V Thangarasa, M Salem, S Saxena, K Leong, J Hestness, S Lie arXiv preprint arXiv:2403.00952, 2024 | | 2024 |
| Learning representations for visual recognition S Saxena Université Grenoble Alpes, 2016 | | 2016 |
| Significance of Dynamic Content of Gait Present in the Lower Silhouette Region S Saxena Biometric Recognition, 159-166, 2011 | | 2011 |
| SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models (Supplementary Material) V Thangarasa, A Gupta, W Marshall, T Li, K Leong, D DeCoste, S Lie, ... | | |
Jakob VerbeekFAIR, Meta在 inria.fr 的电子邮件经过验证
