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Oral
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Wed 1:45
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Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
JIAN XU · Delu Zeng · John Paisley
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Poster
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Wed 2:30
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Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
JIAN XU · Delu Zeng · John Paisley
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Poster
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Wed 2:30
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Total Variation Floodgate for Variable Importance Inference in Classification
Wenshuo Wang · Lucas Janson · Lihua Lei · Aaditya Ramdas
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Poster
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Tue 4:30
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A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
Chengrui Li · Weihan Li · Yule Wang · Anqi Wu
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Poster
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Thu 2:30
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Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution
Johannes Zenn · Robert Bamler
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Poster
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Tue 4:30
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Kernel Semi-Implicit Variational Inference
Ziheng Cheng · Longlin Yu · Tianyu Xie · Shiyue Zhang · Cheng Zhang
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Poster
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Thu 2:30
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Online Variational Sequential Monte Carlo
Alessandro Mastrototaro · Jimmy Olsson
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Workshop
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Stein Variational Newton Neural Network Ensembles
Klemens Flöge · Muhammad Abdul Moeed · Vincent Fortuin
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Workshop
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Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks
Tristan Cinquin · Robert Bamler
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Workshop
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Learning high-dimensional mixed models via amortized variational inference
Priscilla Ong · Manuel Haussmann · Harri Lähdesmäki
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Poster
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Tue 4:30
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Efficient Mixture Learning in Black-Box Variational Inference
Alexandra Hotti · Oskar Kviman · Ricky Molén · Víctor Elvira · Jens Lagergren
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Workshop
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EigenVI: score-based variational inference with orthogonal function expansions
Diana Cai · Chirag Modi · Charles Margossian · Robert Gower · David Blei · Lawrence Saul
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