| Learning activation functions in deep (spline) neural networks P Bohra, J Campos, H Gupta, S Aziznejad, M Unser IEEE Open Journal of Signal Processing 1, 295-309, 2020 | 56 | 2020 |
| A neural-network-based convex regularizer for inverse problems A Goujon, S Neumayer, P Bohra, S Ducotterd, M Unser IEEE Transactions on Computational Imaging, 2023 | 39* | 2023 |
| Continuous-Domain Signal Reconstruction Using -Norm Regularization P Bohra, M Unser IEEE Transactions on Signal Processing 68, 4543-4554, 2020 | 29 | 2020 |
| Learning Lipschitz-controlled activation functions in neural networks for plug-and-play image reconstruction methods PN Bohra, D Perdios, A Goujon, S Emery, M Unser NeurIPS 2021 Workshop on Deep Learning and Inverse Problems, 2021 | 24 | 2021 |
| Approximation of Lipschitz functions using deep spline neural networks S Neumayer, A Goujon, P Bohra, M Unser SIAM Journal on Mathematics of Data Science 5 (2), 306-322, 2023 | 21 | 2023 |
| Improving Lipschitz-constrained neural networks by learning activation functions S Ducotterd, A Goujon, P Bohra, D Perdios, S Neumayer, M Unser Journal of Machine Learning Research 25 (65), 1-30, 2024 | 15 | 2024 |
| Variance-stabilization-based compressive inversion under Poisson or Poisson–Gaussian noise with analytical bounds P Bohra, D Garg, KS Gurumoorthy, A Rajwade Inverse Problems 35 (10), 105006, 2019 | 15* | 2019 |
| Bayesian inversion for nonlinear imaging models using deep generative priors P Bohra, T Pham, J Dong, M Unser IEEE Transactions on Computational Imaging 8, 1237-1249, 2022 | 14 | 2022 |
| Dynamic Fourier ptychography with deep spatiotemporal priors P Bohra, T Pham, Y Long, J Yoo, M Unser Inverse Problems 39 (6), 064005, 2023 | 6 | 2023 |
| Computation of" Best" Interpolants in the Lp Sense P Bohra, M Unser ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 4 | 2020 |
| A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods P Bohra, P del Aguila Pla, JF Giovannelli, M Unser IEEE Transactions on Signal Processing 71, 2043-2055, 2023 | 1 | 2023 |
| Random ReLU Neural Networks as Non-Gaussian Processes R Parhi, P Bohra, AE Biari, M Pourya, M Unser arXiv preprint arXiv:2405.10229, 2024 | | 2024 |
| Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks PN Bohra EPFL, 2024 | | 2024 |
| CRR: Convex Ridge Regularizer A Goujon, S Neumayer, P Bohra, S Ducotterd, M Unser Astrophysics Source Code Library, ascl: 2401.016, 2024 | | 2024 |
| Opportunities and Challenges for Generative Adversarial Reconstruction by Distribution Matching (CryoGAN) M Unser, PN Bohra SIAM Conference on Imaging Science (IS'22), 2022 | | 2022 |
| POISSON LOW-RANK MATRIX RECOVERY USING THE ANSCOMBE TRANSFORM P Bohra, A Rajwade 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018 | | 2018 |
Michael UnserProfessor, Biomedical Imaging Group, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland在 epfl.ch 的电子邮件经过验证
