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Workshop
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Probabilistic predictions with Fourier neural operators
Christopher Bülte · Philipp Scholl · Gitta Kutyniok
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Workshop
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Early Exiting in Deep Neural Networks via Dirichlet-based Uncertainty Quantification
Feng Xia · Jake Snell · Tom Griffiths
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Workshop
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Uncertainty Quantification for Martian Surface Spectral Analysis using Bayesian Deep Learning
Mark Hinds · Michael Geyer · Natalie Klein
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Affinity Event
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Sparse Partial Bayesian Networks: Efficient Uncertainty Quantification in Medical Image Analysis
Zeinab Abboud · Herve Lombaert · Samuel Kadoury
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Workshop
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Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification
Canberk Ekmekci · Tekin Bicer · Zichao Di · Junjing Deng · Mujdat Cetin
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Poster
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Wed 11:00
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Credal Deep Ensembles for Uncertainty Quantification
Kaizheng Wang · Fabio Cuzzolin · Shireen Kudukkil Manchingal - · Keivan Shariatmadar · David Moens · Hans Hallez
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Workshop
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Neural network prediction of strong lensing systems with domain adaptation and uncertainty quantification
Shrihan Agarwal · Aleksandra Ciprijanovic · Brian Nord
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Workshop
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Sat 15:45
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Length Optimization in Conformal Prediction
Shayan Kiyani · George J. Pappas · Hamed Hassani
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Workshop
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Necessity of Uncertainty Quantification for Audio-driven Healthcare Diagnosis
Shubham Kulkarni · Hideaki Watanabe · Fuminori Homma
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Workshop
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Sat 15:45
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Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks
Rachel Longjohn · Giri Gopalan · Emily Casleton
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Poster
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Fri 11:00
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Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
Alexander Nikitin · Jannik Kossen · Yarin Gal · Pekka Marttinen
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Workshop
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Bayesian Outcome Weighted Learning
Nikki Freeman · Sophia Yazzourh
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