Poisson Low-Rank Matrix Recovery Using the Anscombe Transform. - Pakshal Bohra; Ajit Rajwade 001 (GlobalSIP, 2018)

Computation of "Best" Interpolants in the Lp Sense. - Pakshal Bohra; Michael Unser (ICASSP, 2020)

Continuous-Domain Signal Reconstruction Using $L_{p}$-Norm Regularization. - Pakshal Bohra; Michael Unser (IEEE Trans. Signal Process., 2020)

A Neural-Network-Based Convex Regularizer for Image Reconstruction. - Alexis Goujon; Sebastian Neumayer; Pakshal Bohra; Stanislas Ducotterd; Michael Unser (CoRR, 2022)

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors. - Pakshal Bohra; Thanh-An Pham; Jonathan Dong; Michael Unser (IEEE Trans. Computational Imaging, 2022)

A Neural-Network-Based Convex Regularizer for Inverse Problems. - Alexis Goujon; Sebastian Neumayer; Pakshal Bohra; Stanislas Ducotterd; Michael Unser (IEEE Trans. Computational Imaging, 2023)

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods. - Pakshal Bohra; Pol del Aguila Pla; Jean-François Giovannelli; Michael Unser (IEEE Trans. Signal Process., 2023)

Approximation of Lipschitz Functions Using Deep Spline Neural Networks. - Sebastian Neumayer; Alexis Goujon; Pakshal Bohra; Michael Unser (SIAM J. Math. Data Sci., 2023)

Random ReLU Neural Networks as Non-Gaussian Processes. - Rahul Parhi; Pakshal Bohra; Ayoub El Biari; Mehrsa Pourya; Michael Unser (CoRR, 2024)

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions. - Stanislas Ducotterd; Alexis Goujon; Pakshal Bohra; Dimitris Perdios; Sebastian Neumayer; Michael Unser (J. Mach. Learn. Res., 2024)