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22 Results
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Poster
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Tue 17:00 |
Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables Yaniv Yacoby · Weiwei Pan · Finale Doshi-Velez |
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Oral
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Thu 18:56 |
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 |
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference Kyurae Kim · Kaiwen Wu · Jisu Oh · Jacob Gardner |
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Workshop
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Exploring Exchangeable Dataset Amortization for Bayesian Posterior Inference Sarthak Mittal · Niels Bracher · Guillaume Lajoie · Priyank Jaini · Marcus Brubaker |
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Workshop
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Collapsed Inference for Bayesian Deep Learning Zhe Zeng · Guy Van den Broeck |
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Workshop
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GFlowNets for Causal Discovery: an Overview Dragos Cristian Manta · Edward Hu · Yoshua Bengio |
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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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Workshop
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Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network Tristan Deleu · Mizu Nishikawa-Toomey · Jithendaraa Subramanian · Nikolay Malkin · Laurent Charlin · Yoshua Bengio |
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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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Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris Emezue · Alexandre Drouin · Tristan Deleu · Stefan Bauer · Yoshua Bengio |