| Provably convergent plug-and-play quasi-Newton methods HY Tan, S Mukherjee, J Tang, CB Schönlieb SIAM Journal on Imaging Sciences 17 (2), 785-819, 2024 | 36 | 2024 |
| Data-driven mirror descent with input-convex neural networks HY Tan, S Mukherjee, J Tang, CB Schönlieb SIAM Journal on Mathematics of Data Science 5 (2), 558-587, 2023 | 20 | 2023 |
| Noise-free sampling algorithms via regularized Wasserstein proximals HY Tan, S Osher, W Li Research in the Mathematical Sciences 11 (4), 65, 2024 | 11 | 2024 |
| Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging M Carioni, S Mukherjee, HY Tan, J Tang Data-driven Models in Inverse Problems, 2024 | 7 | 2024 |
| Boosting data-driven mirror descent with randomization, equivariance, and acceleration HY Tan, S Mukherjee, J Tang, CB Schönlieb Transactions on Machine Learning Research, 2024 | 7 | 2024 |
| Unsupervised training of convex regularizers using maximum likelihood estimation HY Tan, Z Cai, M Pereyra, S Mukherjee, J Tang, CB Schönlieb arXiv preprint arXiv:2404.05445, 2024 | 6 | 2024 |
| Robust data-driven accelerated mirror descent HY Tan, S Mukherjee, J Tang, A Hauptmann, CB Schönlieb ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 2 | 2023 |
| Dataset Distillation as Pushforward Optimal Quantization HY Tan, E Slade arXiv preprint arXiv:2501.07681, 2025 | 1 | 2025 |
| Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging M Carioni, S Mukherjee, HY Tan, J Tang De Gruyter, 2025 | 1 | 2025 |
| Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds HY Tan, S Mukherjee, J Tang, CB Schönlieb arXiv preprint arXiv:2408.06996, 2024 | 1 | 2024 |
| Solving Imaging Inverse Problems Using Plug-and-Play Denoisers: Regularization and Optimization Perspectives HY Tan, S Mukherjee, J Tang arXiv preprint arXiv:2509.03475, 2025 | | 2025 |
| Preconditioned Regularized Wasserstein Proximal Sampling HY Tan, S Osher, W Li arXiv preprint arXiv:2509.01685, 2025 | | 2025 |
| Designing Provably Convergent Algorithms from the Geometry of Data HY Tan University of Cambridge, 2025 | | 2025 |
Junqi TangAssistant Professor, University of BirminghamVerified email at bham.ac.uk
