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Journal Articles
- 2024
[j4]Ashwini Pokle, Matthew J. Muckley, Ricky T. Q. Chen, Brian Karrer:
Training-free linear image inverses via flows. Trans. Mach. Learn. Res. 2024 (2024)- 2023
- [j3]Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Hervé Jégou:
Image Compression with Product Quantized Masked Image Modeling. Trans. Mach. Learn. Res. 2023 (2023) - 2021
- [j2]Matthew J. Muckley
, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, Florian Knoll:
Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. IEEE Trans. Medical Imaging 40(9): 2306-2317 (2021) - 2015
- [j1]Matthew J. Muckley, Douglas C. Noll, Jeffrey A. Fessler:
Fast Parallel MR Image Reconstruction via B1-Based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA). IEEE Trans. Medical Imaging 34(2): 578-588 (2015)
Conference and Workshop Papers
- 2025
- [c14]Matthew J. Muckley, Marton Havasi, Jakob Verbeek, Karen Ullrich:
Architecture Optimizations for Improving Neural Image Compression Compute Complexity. DCC 2025: 3-12 - [c13]Daniel Severo, Jingtong Su, Anji Liu, Jeff Johnson, Brian Karrer, Guy Van den Broeck, Matthew J. Muckley, Karen Ullrich:
Enhancing and Evaluating Probabilistic Circuits for High-Resolution Lossless Image Compression. DCC 2025: 253-262 - [c12]Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. ICLR 2025 - [c11]Théophane Vallaeys, Matthew J. Muckley, Jakob Verbeek, Matthijs Douze:
Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks. ICLR 2025 - 2024
- [c10]Marlène Careil, Matthew J. Muckley, Jakob Verbeek, Stéphane Lathuilière:
Towards image compression with perfect realism at ultra-low bitrates. ICLR 2024 - [c9]Iris A. M. Huijben, Matthijs Douze, Matthew J. Muckley, Ruud van Sloun, Jakob Verbeek:
Residual Quantization with Implicit Neural Codebooks. ICML 2024 - [c8]Tariq Berrada Ifriqi, Pietro Astolfi, Melissa Hall, Reyhane Askari Hemmat, Yohann Benchetrit, Marton Havasi, Matthew J. Muckley, Karteek Alahari, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal:
On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. NeurIPS 2024 - 2023
- [c7]Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich, Hervé Jégou, Jakob Verbeek:
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models. ICML 2023: 25426-25443 - 2022
- [c6]Tim Bakker, Matthew J. Muckley, Adriana Romero-Soriano, Michal Drozdzal, Luis Pineda:
On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction. MIDL 2022: 63-85 - 2021
- [c5]Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - 2019
- [c4]Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal:
Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition. CVPR 2019: 2049-2058 - [c3]Patricia M. Johnson, Matthew J. Muckley, Mary Bruno, Erich Kobler, Kerstin Hammernik, Thomas Pock, Florian Knoll:
Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions. MLMIR@MICCAI 2019: 71-79 - 2018
- [c2]Erich Kobler, Matthew J. Muckley, Baiyu Chen, Florian Knoll, Kerstin Hammernik, Thomas Pock, Daniel K. Sodickson, Ricardo Otazo:
Variational Deep Learning for Low-Dose Computed Tomography. ICASSP 2018: 6687-6691 - 2014
- [c1]Matthew J. Muckley, Jeffrey A. Fessler:
Fast MR image reconstruction with orthogonal wavelet regularization via shift-variant shrinkage. ICIP 2014: 3651-3655
Informal and Other Publications
- 2025
- [i21]Théophane Vallaeys, Matthew J. Muckley, Jakob Verbeek, Matthijs Douze:
Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks. CoRR abs/2501.03078 (2025) - [i20]Daniel Severo, Giuseppe Ottaviano, Matthew J. Muckley, Karen Ullrich, Matthijs Douze:
Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search. CoRR abs/2501.10479 (2025) - [i19]Revant Teotia, Candace Ross, Karen Ullrich, Sumit Chopra, Adriana Romero-Soriano, Melissa Hall, Matthew J. Muckley:
DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models. CoRR abs/2506.05108 (2025) - [i18]Mido Assran, Adrien Bardes, David Fan, Quentin Garrido, Russell Howes, Mojtaba Komeili, Matthew J. Muckley, Ammar Rizvi, Claire Roberts, Koustuv Sinha, Artem Zholus, Sergio Arnaud, Abha Gejji, Ada Martin, Francois Robert Hogan, Daniel Dugas, Piotr Bojanowski, Vasil Khalidov, Patrick Labatut, Francisco Massa, Marc Szafraniec, Kapil Krishnakumar, Yong Li, Xiaodong Ma, Sarath Chandar, Franziska Meier, Yann LeCun, Michael Rabbat, Nicolas Ballas:
V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. CoRR abs/2506.09985 (2025) - 2024
- [i17]Iris A. M. Huijben, Matthijs Douze, Matthew J. Muckley, Ruud van Sloun, Jakob Verbeek:
Residual Quantization with Implicit Neural Codebooks. CoRR abs/2401.14732 (2024) - [i16]Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon, Céline Hudelot, Armand Joulin, Yann LeCun, Matthew J. Muckley, Maxime Oquab, Marie-Pierre Revel, Maria Vakalopoulou:
Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. CoRR abs/2405.01469 (2024) - [i15]Pietro Astolfi, Marlène Careil, Melissa Hall, Oscar Mañas, Matthew J. Muckley, Jakob Verbeek, Adriana Romero-Soriano, Michal Drozdzal:
Consistency-diversity-realism Pareto fronts of conditional image generative models. CoRR abs/2406.10429 (2024) - [i14]Buu Phan, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Understanding and Mitigating Tokenization Bias in Language Models. CoRR abs/2406.16829 (2024) - [i13]Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. CoRR abs/2410.09303 (2024) - [i12]Tariq Berrada, Pietro Astolfi, Melissa Hall, Reyhane Askari Hemmat, Yohann Benchetrit, Marton Havasi, Matthew J. Muckley, Karteek Alahari, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal:
On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. CoRR abs/2411.03177 (2024) - 2023
- [i11]Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich, Hervé Jégou, Jakob Verbeek:
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models. CoRR abs/2301.11189 (2023) - [i10]Ashwini Pokle, Matthew J. Muckley, Ricky T. Q. Chen, Brian Karrer:
Training-free Linear Image Inversion via Flows. CoRR abs/2310.04432 (2023) - [i9]Marlène Careil, Matthew J. Muckley, Jakob Verbeek, Stéphane Lathuilière:
Towards image compression with perfect realism at ultra-low bitrates. CoRR abs/2310.10325 (2023) - 2022
- [i8]Tim Bakker, Matthew J. Muckley, Adriana Romero-Soriano, Michal Drozdzal, Luis Pineda:
On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction. CoRR abs/2203.16392 (2022) - [i7]Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Hervé Jégou:
Image Compression with Product Quantized Masked Image Modeling. CoRR abs/2212.07372 (2022) - [i6]Ricky T. Q. Chen, Matthew Le, Matthew J. Muckley, Maximilian Nickel, Karen Ullrich:
Latent Discretization for Continuous-time Sequence Compression. CoRR abs/2212.13659 (2022) - 2021
- [i5]Anuroop Sriram, Matthew J. Muckley, Koustuv Sinha, Farah Shamout, Joelle Pineau, Krzysztof J. Geras, Lea Azour, Yindalon Aphinyanaphongs, Nafissa Yakubova, William Moore:
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. CoRR abs/2101.04909 (2021) - 2020
- [i4]Florian Knoll, Tullie Murrell, Anuroop Sriram, Nafissa Yakubova, Jure Zbontar, Michael G. Rabbat, Aaron Defazio, Matthew J. Muckley, Daniel K. Sodickson, C. Lawrence Zitnick, Michael P. Recht:
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. CoRR abs/2001.02518 (2020) - [i3]Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, Florian Knoll:
State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge. CoRR abs/2012.06318 (2020) - 2019
- [i2]Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal:
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition. CoRR abs/1902.03051 (2019) - 2018
- [i1]Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzal, Adriana Romero, Michael G. Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, Yvonne W. Lui:
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. CoRR abs/1811.08839 (2018)
Coauthor Index
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