Martin Benning
Professor of Inverse Problems
Develops optimisation and variational methods for inverse problems and deep learning, including learned regularisation for image reconstruction.
Martin Benning's lab at UCL works on probabilistic & causal inference, signal processing & information theory and 3D vision & neural rendering. 14 papers since 2023, 1 at top venues, mostly ISBI and JMLR.
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 7%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 2 papers2025 · T1 0
- 7 papers2024 · T1 0
- 4 papers2023 · T1 1
T1 venuesOtherVenues: ISBI, JMLR, WACV
Research focuspaper titles that use each topic's words
- 3D vision & neural rendering3 papers
- Signal processing & information theory1 paper
- variational1 paper
- Probabilistic & causal inference0 papers
- image reconstruction0 papers
Paper list
From the lab homepage.
20261 paper
- Handbook of Numerical AnalysisA unified framework for lifted training and inversion approaches (opens in a new tab)
20252 papers
- Winter Conference on Applications of Computer Vision-WACVCAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation (opens in a new tab)
- WACVCompositional Segmentation of Cardiac Images Leveraging Metadata (opens in a new tab)
20247 papers
- MLSPA Lifted Bregman Strategy for Training Unfolded Proximal Neural Network Gaussian Denoisers (opens in a new tab)
- Communications on Applied Mathematics and ComputationConvergent Data-Driven Regularizations for CT Reconstruction (opens in a new tab)
- ISBICrop and Couple: Cardiac Image Segmentation Using Interlinked Specialist Networks (opens in a new tab)
- Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter AcquisitionMisclassification Loss for Segmentation of the Aortic Vessel Tree (opens in a new tab)
- Computer Vision - ECCV European Conference, Milan, Italy, September 29-October 4, , Proceedings, Part LXXIXRAVE: Residual Vector Embedding for CLIP-Guided Backlit Image Enhancement (opens in a new tab)
- Numerical Algebra, Control and OptimizationRegularization of inverse problems: deep equilibrium models versus bilevel learning (opens in a new tab)
- IMA Journal of Applied MathematicsTrust your source: quantifying source condition elements for variational regularisation methods (opens in a new tab)
20234 papers
- Frontiers in Applied Mathematics and StatisticsA lifted Bregman formulation for the inversion of deep neural networks (opens in a new tab)
- Handbook of Mathematical Models and Algorithms in Computer Vision and ImagingBregman Methods for Large-Scale Optimization with Applications in Imaging
- JMLR (T1)Lifted Bregman Training of Neural Networks
- LAScarQSSequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-Based Processing (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UCLFall 2027
Not announced yet
Computer Science MPhil/PhD
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Your notes
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.