Julián Tachella

57 papers A* 7A 1B 1Misc 4Journal 37Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Unrolled Networks for Large-Scale 3D Inverse Problems. CoRR Romain Vo, Julián Tachella
2026	J	`jnl`	Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising. CoRR Brayan Monroy, Jorge Bacca, Julián Tachella
2026	J	`jnl`	Learning to reconstruct from saturated data: audio declipping and high-dynamic range imaging. CoRR Victor Sechaud, Laurent Jacques, Patrice Abry, Julián Tachella
2026	J	`jnl`	Learning to reconstruct from saturated data: audio declipping and high-dynamic range imaging. Trans. Mach. Learn. Res. Victor Sechaud, Laurent Jacques, Patrice Abry, Julián Tachella
2026	J	`jnl`	Multilevel Plug-and-Play Image Restoration. IEEE Trans. Computational Imaging Nils Laurent, Julián Tachella, Elisa Riccietti, Nelly Pustelnik
2026	J	`jnl`	Self-Supervised Learning from Noisy and Incomplete Data. CoRR Julián Tachella, Mike E. Davies
2026	J	`jnl`	UNet-AF: An alias-free UNet for image restoration. CoRR Jérémy Scanvic, Quentin Barthélemy, Julián Tachella
2025	—	`conf`	A Plug-and-Play Approach for Point Cloud Registration. SSP Maurine Bouzeid, Pierre Bruel, Vincent Poulain, Julián Tachella, Jean-Yves Tourneret, David Youssefi
2025	J	`jnl`	DeepInverse: A Python package for solving imaging inverse problems with deep learning. J. Open Source Softw. Julián Tachella, Matthieu Terris, Samuel Hurault, Andrew Wang, Leo Davy, Jérémy Scanvic, Victor Sechaud, Romain Vo, Thomas Moreau, Thomas Davies, Dongdong Chen, Nils Laurent, Brayan Monroy, Jonathan Dong, Zhiyuan Hu, Minh-Hai Nguyen, Florian Sarron, Pierre Weiss, Paul Escande, Mathurin Massias, Thibaut Modrzyk, Brett Levac, Tobías I. Liaudat, Maxime Song, Johannes Hertrich, Sebastian Neumayer, Georg Schramm
2025	J	`jnl`	Equivariant Deep Equilibrium Models for Imaging Inverse Problems. CoRR Alexander Mehta, Ruangrawee Kitichotkul, Vivek K. Goyal, Julián Tachella
2025	J	`jnl`	Equivariant Splitting: Self-supervised learning from incomplete data. CoRR Victor Sechaud, Jérémy Scanvic, Quentin Barthélemy, Patrice Abry, Julián Tachella
2025	A*	`conf`	Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise. CVPR Brayan Monroy, Jorge Bacca, Julián Tachella
2025	J	`jnl`	Reconstruct Anything Model: a lightweight foundation model for computational imaging. CoRR Matthieu Terris, Samuel Hurault, Maxime Song, Julián Tachella
2025	J	`jnl`	Self-supervised learning for phase retrieval. CoRR Victor Sechaud, Patrice Abry, Laurent Jacques, Julián Tachella
2025	Misc	`conf`	Structured Random Model for Fast and Robust Phase Retrieval. ICASSP Zhiyuan Hu, Julián Tachella, Michael Unser, Jonathan Dong
2025	J	`jnl`	Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks. CoRR Jérémy Scanvic, Quentin Barthélemy, Julián Tachella
2025	A*	`conf`	UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate. ICLR Julián Tachella, Mike E. Davies, Laurent Jacques
2024	—	`conf`	Equivariance-Based Self-Supervised Learning for Audio Signal Recovery from Clipped Measurements. EUSIPCO Victor Sechaud, Laurent Jacques, Patrice Abry, Julián Tachella
2024	J	`jnl`	Equivariance-based self-supervised learning for audio signal recovery from clipped measurements. CoRR Victor Sechaud, Laurent Jacques, Patrice Abry, Julián Tachella
2024	A*	`conf`	Equivariant Plug-and-Play Image Reconstruction. CVPR Matthieu Terris, Thomas Moreau, Nelly Pustelnik, Julián Tachella
2024	A	`conf`	Equivariant bootstrapping for uncertainty quantification in imaging inverse problems. AISTATS Marcelo Pereyra, Julián Tachella
2024	—	`conf`	From Linear to Nonlinear Unfolded Condat-Vú Algorithm for Spectro-Polarimetric Hight-Constrast Image Recovery. EUSIPCO E. Chappon, Nelly Pustelnik, Julián Tachella, Laurence Denneulin, A. Ferrari, Maud Langlois
2024	J	`jnl`	Spline Sketches: An Efficient Approach for Photon Counting Lidar. IEEE Trans. Computational Imaging Michael P. Sheehan, Julián Tachella, Mike E. Davies
2024	J	`jnl`	UNSURE: Unknown Noise level Stein's Unbiased Risk Estimator. CoRR Julián Tachella, Mike E. Davies, Laurent Jacques
2023	J	`jnl`	Equivariant Bootstrapping for Uncertainty Quantification in Imaging Inverse Problems. CoRR Julián Tachella, Marcelo Pereyra
2023	J	`jnl`	Equivariant plug-and-play image reconstruction. CoRR Matthieu Terris, Thomas Moreau, Nelly Pustelnik, Julián Tachella
2023	Misc	`conf`	Hardware Friendly Spline Sketched Lidar. ICASSP Michael P. Sheehan, Julián Tachella, Mike E. Davies
2023	J	`jnl`	Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning. IEEE Signal Process. Mag. Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry, Julián Tachella
2023	J	`jnl`	Learning to Reconstruct Signals From Binary Measurements. CoRR Julián Tachella, Laurent Jacques
2023	J	`jnl`	Learning to reconstruct signals from binary measurements alone. Trans. Mach. Learn. Res. Julián Tachella, Laurent Jacques
2023	J	`jnl`	Self-Supervised Learning for Image Super-Resolution and Deblurring. CoRR Jérémy Scanvic, Mike E. Davies, Patrice Abry, Julián Tachella
2023	J	`jnl`	Sensing Theorems for Unsupervised Learning in Linear Inverse Problems. J. Mach. Learn. Res. Julián Tachella, Dongdong Chen, Mike E. Davies
2022	J	`jnl`	Imaging with Equivariant Deep Learning. CoRR Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry, Julián Tachella
2022	A*	`conf`	Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements. CVPR Dongdong Chen, Julián Tachella, Mike E. Davies
2022	J	`jnl`	Sampling Theorems for Learning from Incomplete Measurements. CoRR Julián Tachella, Dongdong Chen, Mike E. Davies
2022	J	`jnl`	Sampling Theorems for Unsupervised Learning in Linear Inverse Problems. CoRR Julián Tachella, Dongdong Chen, Mike E. Davies
2022	Misc	`conf`	Sketched RT3D: How to Reconstruct Billions of Photons Per Second. ICASSP Julián Tachella, Michael P. Sheehan, Mike E. Davies
2022	J	`jnl`	Sketched RT3D: How to reconstruct billions of photons per second. CoRR Julián Tachella, Michael P. Sheehan, Mike E. Davies
2022	A*	`conf`	Unsupervised Learning From Incomplete Measurements for Inverse Problems. NeurIPS Julián Tachella, Dongdong Chen, Mike E. Davies
2021	J	`jnl`	A Sketching Framework for Reduced Data Transfer in Photon Counting Lidar. IEEE Trans. Computational Imaging Michael P. Sheehan, Julián Tachella, Mike E. Davies
2021	B	`conf`	Edge-Resolved Transient Imaging: Performance Analyses, Optimizations, and Simulations. ICIP Charles Saunders, William Krska, Julián Tachella, Sheila W. Seidel, Joshua Rapp, John Murray-Bruce, Yoann Altmann, Steve McLaughlin, Vivek K. Goyal
2021	A*	`conf`	Equivariant Imaging: Learning Beyond the Range Space. ICCV Dongdong Chen, Julián Tachella, Mike E. Davies
2021	J	`jnl`	Equivariant Imaging: Learning Beyond the Range Space. CoRR Dongdong Chen, Julián Tachella, Mike E. Davies
2021	J	`jnl`	Robust 3D Reconstruction of Dynamic Scenes From Single-Photon Lidar Using Beta-Divergences. IEEE Trans. Image Process. Quentin Legros, Julián Tachella, Rachael Tobin, Aongus McCarthy, Sylvain Meignen, Gerald S. Buller, Yoann Altmann, Steve McLaughlin, Michael E. Davies
2021	J	`jnl`	Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements. CoRR Dongdong Chen, Julián Tachella, Mike E. Davies
2021	—	`conf`	Surface Detection for Sketched Single Photon Lidar. EUSIPCO Michael P. Sheehan, Julián Tachella, Mike E. Davies
2021	A*	`conf`	The Neural Tangent Link Between CNN Denoisers and Non-Local Filters. CVPR Julián Tachella, Junqi Tang, Mike E. Davies
2020	J	`jnl`	Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances. IEEE Signal Process. Mag. Joshua Rapp, Julián Tachella, Yoann Altmann, Stephen McLaughlin, Vivek K. Goyal
2020	J	`jnl`	Bayesian 3D Reconstruction of Subsampled Multispectral Single-Photon Lidar Signals. IEEE Trans. Computational Imaging Julián Tachella, Yoann Altmann, Miguel Marquez, Henry Arguello Fuentes, Jean-Yves Tourneret, Steve McLaughlin
2020	J	`jnl`	CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser. CoRR Julián Tachella, Junqi Tang, Mike E. Davies
2020	J	`jnl`	Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences. CoRR Quentin Legros, Julián Tachella, Rachael Tobin, Aongus McCarthy, Sylvain Meignen, Gerald S. Buller, Yoann Altmann, Stephen McLaughlin, Michael E. Davies
2020	J	`jnl`	Seeing Around Corners with Edge-Resolved Transient Imaging. CoRR Joshua Rapp, Charles Saunders, Julián Tachella, John Murray-Bruce, Yoann Altmann, Jean-Yves Tourneret, Stephen McLaughlin, Robin M. A. Dawson, Franco N. C. Wong, Vivek K. Goyal
2019	Misc	`conf`	3D Reconstruction Using Single-photon Lidar Data Exploiting the Widths of the Returns. ICASSP Julián Tachella, Yoann Altmann, Steve McLaughlin, Jean-Yves Tourneret
2019	J	`jnl`	Bayesian 3D Reconstruction of Complex Scenes from Single-Photon Lidar Data. SIAM J. Imaging Sci. Julián Tachella, Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller, Steve McLaughlin, Jean-Yves Tourneret
2019	—	`conf`	Fast Surface Detection in Single-Photon Lidar Waveforms. EUSIPCO Julián Tachella, Yoann Altmann, Steve McLaughlin, Jean-Yves Tourneret
2019	—	`conf`	Real-Time 3D Color Imaging with Single-Photon Lidar Data. CAMSAP Julián Tachella, Yoann Altmann, Stephen McLaughlin, Jean-Yves Tourneret
2018	—	`conf`	Bayesian Restoration of High-Dimensional Photon-Starved Images. EUSIPCO Julián Tachella, Yoann Altmann, Marcelo Pereyra, Stephen McLaughlin, Jean-Yves Tourneret