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Showing papers from University of Tuebingen Show all papers

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Foveated BagNet: Inherent Interpretability Does Not Exclude Global Context

Holger Heidrich, Sarah Müller, Andreas Schilling

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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medium 0/10
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45%Niche pick
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Understanding Multi-View Transformers

Julien Gaubil, Michal Stary, Louis Martinez, Andreas Geiger and 3 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
83%Must read
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Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation

MA-BC partitions conflicting expert trajectories while pooling compatible data to recover Pareto-optimal policies in multi-objective imitation with minimax optimal rates.

Ziyad Sheebaelhamd, Luca Viano, Volkan Cevher, Claire Vernade

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 3/5
medium 8/10
strict 2/5
89%Must read
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SAMoR: Motion Modelling for Articulated Objects of Any Skeleton and Topology

SAMoR encodes cross-topology articulated motion into shared part tokens via graph-transformer encoding and attention supervision, achieving 5.8× lower reconstruction error than adapted baselines across arbitrary skeletons.

Yuhao Zhang, Gerard Pons-Moll, Tolga Birdal

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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16/20 AI panelreviewers recommend it

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AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 1/5
80%Must read
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Conditioning Gaussian Processes on Almost Anything

Gaussian processes are recast as linear diffusion models to enable conditioning on arbitrary likelihoods, including language and physics, via ODE sampling without bespoke derivations.

Henry Moss, Lachlan Astfalck, Tom Cowperthwaite, Colin Doumont and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 2/5
74%Highly rated
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Closed-Form Last Layer Optimization

Closed-form last-layer optimization treats final weights as backbone-dependent functions, yielding convergence guarantees and outperforming SGD and Adam on regression tasks.

Alexandre Galashov, Nathaël Da Costa, Liyuan Xu, Philipp Hennig and 1 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 3/10
strict 2/5