Bayesian Restoration of High-Dimensional Photon-Starved Images. - Julián Tachella; Yoann Altmann; Marcelo Pereyra; Stephen McLaughlin 001; Jean-Yves Tourneret (EUSIPCO, 2018)

Real-Time 3D Color Imaging with Single-Photon Lidar Data. - Julián Tachella; Yoann Altmann; Stephen McLaughlin 001; Jean-Yves Tourneret (CAMSAP, 2019)

Fast Surface Detection in Single-Photon Lidar Waveforms. - Julián Tachella; Yoann Altmann; Steve McLaughlin 001; Jean-Yves Tourneret (EUSIPCO, 2019)

3D Reconstruction Using Single-photon Lidar Data Exploiting the Widths of the Returns. - Julián Tachella; Yoann Altmann; Steve McLaughlin 001; Jean-Yves Tourneret (ICASSP, 2019)

Bayesian 3D Reconstruction of Complex Scenes from Single-Photon Lidar Data. - Julián Tachella; Yoann Altmann; Ximing Ren; Aongus McCarthy; Gerald S. Buller; Steve McLaughlin 001; Jean-Yves Tourneret (SIAM J. Imaging Sci., 2019)

Seeing Around Corners with Edge-Resolved Transient Imaging. - Joshua Rapp; Charles Saunders; Julián Tachella; John Murray-Bruce; Yoann Altmann; Jean-Yves Tourneret; Stephen McLaughlin 001; Robin M. A. Dawson; Franco N. C. Wong; Vivek K. Goyal (CoRR, 2020)

CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser. - Julián Tachella; Junqi Tang; Mike E. Davies 001 (CoRR, 2020)

Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances. - Joshua Rapp; Julián Tachella; Yoann Altmann; Stephen McLaughlin 001; Vivek K. Goyal (IEEE Signal Process. Mag., 2020)

Bayesian 3D Reconstruction of Subsampled Multispectral Single-Photon Lidar Signals. - Julián Tachella; Yoann Altmann; Miguel Marquez; Henry Arguello Fuentes; Jean-Yves Tourneret; Steve McLaughlin 001 (IEEE Trans. Computational Imaging, 2020)

The Neural Tangent Link Between CNN Denoisers and Non-Local Filters. - Julián Tachella; Junqi Tang; Mike E. Davies 001 (CVPR, 2021)

Surface Detection for Sketched Single Photon Lidar. - Michael P. Sheehan; Julián Tachella; Mike E. Davies 001 (EUSIPCO, 2021)

Equivariant Imaging: Learning Beyond the Range Space. - Dongdong Chen 004; Julián Tachella; Mike E. Davies 001 (ICCV, 2021)

Edge-Resolved Transient Imaging: Performance Analyses, Optimizations, and Simulations. - Charles Saunders; William Krska; Julián Tachella; Sheila W. Seidel; Joshua Rapp; John Murray-Bruce; Yoann Altmann; Steve McLaughlin 001; Vivek K. Goyal (ICIP, 2021)

A Sketching Framework for Reduced Data Transfer in Photon Counting Lidar. - Michael P. Sheehan; Julián Tachella; Mike E. Davies 001 (IEEE Trans. Computational Imaging, 2021)

Robust 3D Reconstruction of Dynamic Scenes From Single-Photon Lidar Using Beta-Divergences. - Quentin Legros; Julián Tachella; Rachael Tobin; Aongus McCarthy; Sylvain Meignen; Gerald S. Buller; Yoann Altmann; Steve McLaughlin 001; Michael E. Davies 001 (IEEE Trans. Image Process., 2021)

Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements. - Dongdong Chen 004; Julián Tachella; Mike E. Davies 001 (CVPR, 2022)

Sketched RT3D: How to Reconstruct Billions of Photons Per Second. - Julián Tachella; Michael P. Sheehan; Mike E. Davies 001 (ICASSP, 2022)

Unsupervised Learning From Incomplete Measurements for Inverse Problems. - Julián Tachella; Dongdong Chen 004; Mike E. Davies 001 (NeurIPS, 2022)

Sampling Theorems for Learning from Incomplete Measurements. - Julián Tachella; Dongdong Chen 004; Mike E. Davies 001 (CoRR, 2022)

Sampling Theorems for Unsupervised Learning in Linear Inverse Problems. - Julián Tachella; Dongdong Chen 004; Mike E. Davies 001 (CoRR, 2022)

Imaging with Equivariant Deep Learning. - Dongdong Chen 004; Mike E. Davies 001; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Ferdia Sherry; Julián Tachella (CoRR, 2022)

Hardware Friendly Spline Sketched Lidar. - Michael P. Sheehan; Julián Tachella; Mike E. Davies 001 (ICASSP, 2023)

Learning to Reconstruct Signals From Binary Measurements. - Julián Tachella; Laurent Jacques (CoRR, 2023)

Self-Supervised Learning for Image Super-Resolution and Deblurring. - Jérémy Scanvic; Mike E. Davies 001; Patrice Abry; Julián Tachella (CoRR, 2023)

Sensing Theorems for Unsupervised Learning in Linear Inverse Problems. - Julián Tachella; Dongdong Chen 004; Mike E. Davies 001 (J. Mach. Learn. Res., 2023)

Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning. - Dongdong Chen 004; Mike E. Davies 001; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Ferdia Sherry; Julián Tachella (IEEE Signal Process. Mag., 2023)

Learning to reconstruct signals from binary measurements alone. - Julián Tachella; Laurent Jacques (Trans. Mach. Learn. Res., 2023)

Equivariant bootstrapping for uncertainty quantification in imaging inverse problems. - Marcelo Pereyra; Julián Tachella (AISTATS, 2024)

Equivariant Plug-and-Play Image Reconstruction. - Matthieu Terris; Thomas Moreau 001; Nelly Pustelnik; Julián Tachella (CVPR, 2024)

Equivariance-Based Self-Supervised Learning for Audio Signal Recovery from Clipped Measurements. - Victor Sechaud; Laurent Jacques; Patrice Abry; Julián Tachella (EUSIPCO, 2024)

UNSURE: Unknown Noise level Stein's Unbiased Risk Estimator. - Julián Tachella; Mike E. Davies 001; Laurent Jacques (CoRR, 2024)

Spline Sketches: An Efficient Approach for Photon Counting Lidar. - Michael P. Sheehan; Julián Tachella; Mike E. Davies 001 (IEEE Trans. Computational Imaging, 2024)

Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise. - Brayan Monroy; Jorge Bacca; Julián Tachella (CVPR, 2025)

Structured Random Model for Fast and Robust Phase Retrieval. - Zhiyuan Hu; Julián Tachella; Michael Unser; Jonathan Dong (ICASSP, 2025)

UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate. - Julián Tachella; Mike E. Davies 001; Laurent Jacques (ICLR, 2025)

A Plug-and-Play Approach for Point Cloud Registration. - Maurine Bouzeid; Pierre Bruel; Vincent Poulain; Julián Tachella; Jean-Yves Tourneret; David Youssefi (SSP, 2025)

Reconstruct Anything Model: a lightweight foundation model for computational imaging. - Matthieu Terris; Samuel Hurault; Maxime Song; Julián Tachella (CoRR, 2025)

Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks. - Jérémy Scanvic; Quentin Barthélemy; Julián Tachella (CoRR, 2025)