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Poster
Wed 11:00 Bayesian Adaptive Calibration and Optimal Design
Rafael Oliveira · Dino Sejdinovic · David Howard · Edwin Bonilla
Workshop
Efficient Bayesian Additive Regression Models For Microbiome and Gene Expression Studies
Tinghua Chen · Michelle Nixon · Justin Silverman
Workshop
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Alan Amin · Nate Gruver · Yucen Li · Yilun Kuang · Hunter Elliott · Calvin McCarter · Aniruddh Raghu · Peyton Greenside · Andrew Wilson
Poster
Thu 16:30 FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
Tristan Cinquin · Marvin Pförtner · Vincent Fortuin · Philipp Hennig · Robert Bamler
Workshop
Evaluating Sparse Galaxy Simulations via Out-of-Distribution Detection and Amortized Bayesian Model Comparison
Lingyi Zhou · Stefan Radev · William H. Oliver · Aura Obreja · Zehao Jin · Tobias Buck
Workshop
Sat 15:45 Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks
Rachel Longjohn · Giri Gopalan · Emily Casleton
Poster
Thu 11:00 BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
Yibin Wang · Haizhou Shi · Ligong Han · Dimitris Metaxas · Hao Wang
Poster
Fri 16:30 Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information
Marco Miani · Lorenzo Beretta · Søren Hauberg
Poster
Thu 11:00 Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
Jinlin Lai · Justin Domke · Daniel Sheldon
Poster
Wed 16:30 Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
Chaeyun Jang · Hyungi Lee · Jungtaek Kim · Juho Lee
Workshop
TP2DP2: A Bayesian Mixture Model of Temporal Point Processes with Determinantal Point Process Prior
Yiwei Dong · Shaoxin Ye · Yuwen Cao · Qiyu Han · Hongteng Xu · Hanfang Yang
Workshop
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna · Sergio Calvo Ordoñez · Felix Opolka · Pietro Lió · José Miguel Hernández-Lobato