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Poster
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Thu 13:30
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MixFlows: principled variational inference via mixed flows
Zuheng Xu · Naitong Chen · Trevor Campbell
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Workshop
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Attention as Implicit Structural Inference
Ryan Singh · Christopher Buckley
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Poster
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Thu 13:30
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Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space
Michael Diao · Krishna Balasubramanian · Sinho Chewi · Adil Salim
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Workshop
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Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Balhae Kim · Hyungi Lee · Juho Lee
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Oral
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Thu 18:56
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Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference
Kyurae Kim · Kaiwen Wu · Jisu Oh · Jacob Gardner
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Poster
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Tue 14:00
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Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference
Kyurae Kim · Kaiwen Wu · Jisu Oh · Jacob Gardner
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Poster
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Tue 14:00
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Free-Form Variational Inference for Gaussian Process State-Space Models
Xuhui Fan · Edwin V. Bonilla · Terence O'kane · Scott SIsson
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Workshop
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BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery
Yashas Annadani · Nick Pawlowski · Joel Jennings · Stefan Bauer · Cheng Zhang · Wenbo Gong
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Workshop
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PITS: Variational Pitch Inference Without Fundamental Frequency for End-to-End Pitch-Controllable TTS
Junhyeok Lee · Wonbin Jung · Hyunjae Cho · Jaeyeon Kim · Jaehwan Kim
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Workshop
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Dimensionality Reduction as Probabilistic Inference
Aditya Ravuri · Francisco Vargas · Vidhi Ramesh · Neil Lawrence
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