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Showing papers from Lancaster University / University of Cambridge Show all papers

83%Must read
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NeurIPS 2026U British ColumbiaTübingen AI CenterU OxfordInstaDeep ResearchU PennsylvaniaControllable generation

Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization

Exploiting spherical latent geometry yields nearly closed-form Bayesian optimization with 100x speedups and matching performance in generative discovery pipelines.

Donney Fan, Colin Doumont, Aleksandra Kalisz, Paul Duckworth and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · 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 4/5
medium 7/10
strict 2/5
71%Highly rated
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NeurIPS 2026Imperial College LondonLancaster University / UniversitLancasterMolecules & drug discovery

Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights

AB-SID-iVAR actively learns Gaussian process targets under unknown self-induced Boltzmann weights, achieving vanishing terminal prediction error without partition function estimation.

Jixiang Qing, Henry Moss, Matthias Sachs

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

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7/20 AI panelreviewers recommend it

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AI panel: 7 of 20 reviewers recommend it
lenient 3/5
medium 3/10
strict 1/5
80%Must read
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NeurIPS 2026Lancaster University / UniversitU New South WalesU CambridgeTübingen AI CenterUniversity Of CambridgeKernels & Gaussian processes

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