Advances in Approximate Bayesian Inference

NIPS 2016 Workshop; December 9, 2016
Room 112, Centre Convencions Internacional Barcelona, Barcelona, Spain

Papers listed here are for archival purposes and do not constitute a proceedings for this workshop.

  1. Proximity Variational Inference
    Jaan Altosaar, Rajesh Ranganath, David Blei
  2. Truncation error of a superposed gamma process in a decreasing order representation Slides
    Julyan Arbel, Igor Prünster
  3. Adaptive construction of measure transports for Bayesian inference
    Daniele Bigoni, Alessio Spantini, Youssef Marzouk
  4. Truncation-free Hybrid Inference for DPMM
    Arnim Bleier
  5. Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation Poster
    Thomas Brouwer, Jes Frellsen, Pietro Lio
  6. Stochastic Gradient Estimation With Finite Differences
    Lars Buesing, Theophane Weber, Shakir Mohamed
  7. Black-box $\alpha$-divergence for Deep Generative Models
    Thang Bui, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Yingzhen Li, Richard E. Turner
  8. Self-Averaging Expectation Propagation
    Burak Cakmak, Manfred Opper, Bernard Fleury, Ole Winther
  9. Variational Lossy Autoencoder
    Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
  10. Measuring the non-asymptotic convergence of sequential Monte Carlo samplers using probabilistic programming Poster
    Marco Cusumano-Towner, Vikash Mansinghka
  11. Expectation Propagation performs a smoothed gradient descent
    Guillaume Dehaene
  12. Approximate Bayesian Binary, Ordinal Regression with Structured Uncertainty in the Inputs
    Aleksandar Dimitriev, Erik Štrumbelj
  13. Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling Poster
    Christophe Dupuy, Francis Bach
  14. A Nearly-Black-Box Online Algorithm for Joint Parameter, State Estimation in Temporal Models
    Yusuf Erol, Yi Wu, Lei Li, Stuart Russell
  15. Smoothing Estimates of Diffusion Processes Poster Slides
    Hans-Christian Ruiz Euler, Hilbert J. Kappen
  16. Robust Variational Inference Poster
    Michael Figurnov, Kirill Struminsky, Dmitry Vetrov
  17. Fast Measurements of Robustness to Changing Priors in Variational Bayes
    Ryan Giordano, Tamara Broderick, Michael Jordan
  18. Continuously tempered Hamiltonian Monte Carlo
    Matthew Graham, Amos Storkey
  19. Boosting Variational Inference Poster
    Fangjian Guo, Xiangyu Wang, Kai Fan, Tamara Broderick, David Dunson
  20. Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation
    Leonard Hasenclever, Stefan Webb, Thibaut Lienart, Sebastian Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh
  21. ELBO surgery: yet another way to carve up the variational evidence lower bound Poster
    Matthew Hoffman, Matthew Johnson
  22. Scalable Inference in Dynamic Mixture Models Poster
    Patrick Jähnichen, Florian Wenzel, Marius Kloft
  23. Differentially Private Automatic Differentiation Variational Inference (DP-ADVI) Poster
    Joonas Jälkö, Onur Dikmen, Antti Honkela
  24. ELFI: Engine for Likelihood-Free Inference
    Antti Kangasrääsiö, Jarno Lintusaari, Kusti Skytén, Henri Vuollekoski, Michael Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski
  25. Adversarial Message Passing For Generative Models
    Theofanis Karaletsos
  26. Improved Particle Filters for Vehicle Localisation Poster
    Kira Kempinska, John Shawe-Taylor
  27. Fixed Point Solutions of Belief Propagation
    Christian Knoll, Franz Pernkopf, Dhagash Mehta, Tianran Chen
  28. Inference and Introspection in Deep Generative Models of Sparse Data Poster
    Rahul Krishnan, Matthew Hoffman
  29. Neural Variational Random Field Learning
    Volodymyr Kuleshov, Stefano Ermon
  30. Wild Variational Approximations Poster
    Yingzhen Li, Qiang Liu
  31. A Unifying Approximate Inference Framework from Variational Free Energy Relaxation Poster
    Yingzhen Li, Richard E. Turner
  32. Stein Variational Gradient Descent: Theory and Applications
    Qiang Liu
  33. B3O: Bayes Empirical Bayes by Bayesian Optimization
    James McInerney
  34. Variational Boosting: Iteratively Refining Posterior Approximations
    Andrew Miller, Nicholas Foti, Ryan Adams
  35. Symmetrized Variational Inference Poster
    David A. Moore
  36. Rejection Sampling Variational Inference
    Christian Andersson Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei
  37. Approximate Recursive Identification of Autoregressive Systems with Skewed Innovations Poster
    Henri Nurminen, Tohid Ardeshiri
  38. On the Pitfalls of Nested Monte Carlo Poster
    Tom Rainforth, Rob Cornish, Hongseok Yang, Frank Wood
  39. Sticking the Landing: A Simple Reduced-Variance Gradient for ADVI Poster
    Geoffrey Roeder, Yuhuai Wu, David Duvenaud
  40. A Deterministic Global Optimization Method for Variational Inference
    Hachem Saddiki, Andrew Trapp, Patrick Flaherty
  41. Re-using gradient computation in automatic variational inference Poster
    Joseph Sakaya, Arto Klami
  42. Modular construction of Bayesian inference algorithms Poster
    Adam Scibior, Zoubin Ghahramani
  43. Bottleneck Conditional Density Estimators
    Rui Shu, Hung Bui, Mohammad Ghavamzadeh
  44. Variational inference via decomposable transports: algorithms for Bayesian filtering and smoothing
    Alessio Spantini, Daniele Bigoni, Youssef Marzouk
  45. Understanding Covariance Estimates in Expectation Propagation
    William Stephenson, Tamara Broderick
  46. Online Inference in Bayesian Non-Parametric Mixture Models under Small Variance Asymptotics Poster
    Ajay Kumar Tanwani, Sylvain Calinon
  47. Parametric Inverse Simulation
    Zenna Tavares, Armando Solar Lezama
  48. Circular Pseudo-Point Approximations for Scaling Gaussian Processes
    William Tebbutt, Thang Bui, Richard Turner
  49. Optimal Control of Network Structure Growth Poster
    Dominik Thalmeier, Vicenç Gómez, Hilbert J. Kappen
  50. Combine Monte Carlo with Exhaustive Search: Effective Variational Inference and Policy Gradient Reinforcement Learning
    Michalis Titsias
  51. Training Deep Gaussian Processes with Sampling Poster
    Keyon Vafa
  52. Learning doubly intractable latent variable models via score matching Poster
    Eszter Vertes, Maneesh Sahani
  53. Scalable Approximate Inference for the Bayesian Nonlinear Support Vector Machine Poster
    Florian Wenzel, Matthäus Deutsch, Théo Galy-Fajou, Marius Kloft
  54. Approximate Inference for Generic Likelihoods via Density-Preserving GMM Simplification Poster
    Lei Yu, Tianyu Yang, Antoni Chan
  55. Balanced Population Stochastic Variational Inference
    Cheng Zhang, Stephan Mandt, Hedvig Kjellstrom
  56. Variable Clamping for Optimization-based Inference Poster
    Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
  57. Online Spike-and-slab Inference with Stochastic Expectation Propagation Poster
    Shandian Zhe, Kuang-Chih Lee, Kai Zhang, Jennifer Neville