no code implementations • 12 Apr 2024 • Lorenc Kapllani, Long Teng
This is motivated by the fact that differential deep learning can provide an efficient approximation of the labels and their derivatives with respect to inputs.
no code implementations • 1 Apr 2024 • Liu Yang, Huiyu Duan, Long Teng, Yucheng Zhu, Xiaohong Liu, Menghan Hu, Xiongkuo Min, Guangtao Zhai, Patrick Le Callet
Finally, we conduct a benchmark experiment to evaluate the performance of state-of-the-art IQA models on our database.
no code implementations • 5 Oct 2023 • Lorenc Kapllani, Long Teng, Matthias Rottmann
In this work, we study uncertainty quantification (UQ) for a class of deep learning-based BSDE schemes.
1 code implementation • 30 Mar 2023 • Huiyu Duan, Wei Shen, Xiongkuo Min, Danyang Tu, Long Teng, Jia Wang, Guangtao Zhai
Recently, masked autoencoders (MAE) for feature pre-training have further unleashed the potential of Transformers, leading to state-of-the-art performances on various high-level vision tasks.
Ranked #4 on Image Defocus Deblurring on DPD (Dual-view)
no code implementations • 3 Oct 2020 • Lorenc Kapllani, Long Teng
In this work, we propose a new deep learning-based scheme for solving high dimensional nonlinear backward stochastic differential equations (BSDEs).