• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 26 matches

• 2020
• 
  Cheng Zhang, Francisco J. R. Ruiz, Thang D. Bui, Adji Bousso Dieng, Dawen Liang:
  Symposium on Advances in Approximate Bayesian Inference, AABI 2019, Vancouver, BC, Canada, December 8, 2019. Proceedings of Machine Learning Research 118, PMLR 2020 [contents]
• 2019
• 
  Alexander A. Alemi:
  Variational Predictive Information Bottleneck. AABI 2019: 1-6
• 
  Pavel Berkovich, Eric Perim, Wessel P. Bruinsma:
  GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models. AABI 2019: 1-14
• 
  Badr-Eddine Chérief-Abdellatif, Pierre Alquier:
  MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy. AABI 2019: 1-21
• 
  Tor Erlend Fjelde, Kai Xu, Mohamed Tarek, Sharan Yalburgi, Hong Ge:
  Bijectors.jl: Flexible transformations for probability distributions. AABI 2019: 1-17
• 
  Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Megha Nawhal, Thibaut Durand, Greg Mori:
  Variational Selective Autoencoder. AABI 2019: 1-17
• 
  Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
  Variational Bayesian Methods for Stochastically Constrained System Design Problems. AABI 2019: 1-12
• 
  He Jia, Uros Seljak:
  Normalizing Constant Estimation with Gaussianized Bridge Sampling. AABI 2019: 1-14
• 
  Vidhi Lalchand, Carl Edward Rasmussen:
  Approximate Inference for Fully Bayesian Gaussian Process Regression. AABI 2019: 1-12
• 
  Xuechen Li, Ting-Kam Leonard Wong, Ricky T. Q. Chen, David Duvenaud:
  Scalable Gradients and Variational Inference for Stochastic Differential Equations. AABI 2019: 1-28
• 
  Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang:
  HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals. AABI 2019: 1-8
• 
  Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt:
  Improving Sequential Latent Variable Models with Autoregressive Flows. AABI 2019: 1-16
• 
  Gonzalo E. Mena, Erdem Varol, Amin Nejatbakhsh, Eviatar Yemini, Liam Paninski:
  Sinkhorn Permutation Variational Marginal Inference. AABI 2019: 1-9
• 
  Ari Pakman, Yueqi Wang, Liam Paninski:
  Neural Permutation Processes. AABI 2019: 1-7
• 
  Michael Pearce:
  The Gaussian Process Prior VAE for Interpretable Latent Dynamics from Pixels. AABI 2019: 1-12
• 
  Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri:
  MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. AABI 2019: 1-36
• 
  Rishit Sheth, Roni Khardon:
  Pseudo-Bayesian Learning via Direct Loss Minimization with Applications to Sparse Gaussian Process Models. AABI 2019: 1-18
• 
  Ravid Shwartz-Ziv, Alexander A. Alemi:
  Information in Infinite Ensembles of Infinitely-Wide Neural Networks. AABI 2019: 1-17
• 
  Mark van der Wilk, S. T. John, Artem Artemev, James Hensman:
  Variational Gaussian Process Models without Matrix Inverses. AABI 2019: 1-9
• 
  Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani:
  AdvancedHMC.jl: A robust, modular and e cient implementation of advanced HMC algorithms. AABI 2019: 1-10
• 
  Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez:
  Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders. AABI 2019: 1-17
• 
  Lily H. Zhang, Michael C. Hughes:
  Rapid Model Comparison by Amortizing Across Models. AABI 2019: 1-11
• 
  Francisco J. R. Ruiz, Cheng Zhang, Dawen Liang, Thang D. Bui:
  Symposium on Advances in Approximate Bayesian Inference, AABI 2018, Montréal, QC, Canada, December 2, 2018. Proceedings of Machine Learning Research 96, PMLR 2019 [contents]
• 2018
• 
  Luigi Acerbi:
  An Exploration of Acquisition and Mean Functions in Variational Bayesian Monte Carlo. AABI 2018: 1-10
• 
  Badr-Eddine Chérief-Abdellatif:
  Consistency of ELBO maximization for model selection. AABI 2018: 11-31
• 
  Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos, Jakob H. Macke:
  Likelihood-free inference with emulator networks. AABI 2018: 32-53