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Showing papers from University of Delaware Show all papers

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NeurIPS 2026Carnegie MellonU DelawareCMU, Carnegie MellonDeep learning theory

Beyond Eigenfunctions: Divergence Principal Functions for Representation Learning

Ritabrata Ray, Sahil Dharod, Burak Varıcı, Nicholas Boffi and 1 more

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

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NeurIPS 2026DurhamU DalhousieU DelawareFlorida InternationalBayesian & probabilistic methods

A Revisit of Hamiltonian Monte Carlo Efficiency on Bayesian Neural Networks

Cuong Ngoc Nguyen, Lam Ho, Vu Dinh, Georgios Karagiannis and 1 more

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

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NeurIPS 2026U DelawareMicrosoftInstruction tuning

When Does Subspace Direction Matter for LoRA? Regime Analysis of the Magnitude Principle in Few-Shot Adaptation

Nischal Subedi, Cencheng Shen, Peng Zhao

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U DelawareU FloridaDistribution shift & OOD detection

A Systematic Analysis of Out-of-Distribution Detection Under Representation and Training Paradigm Shifts

A systematic benchmark shows out-of-distribution detector competitiveness depends mainly on learned representations rather than score design, with neural collapse metrics predicting top detector choices without extra out-of-distribution data.

Claudio César Claros-Olivares, Austin Brockmeier

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 16 of 20 reviewers recommend it
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