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Poster
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Tue 7:00 |
Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization Richard Zhang, Daniel Golovin |
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Poster
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Tue 7:00 |
Recurrent Hierarchical Topic-Guided RNN for Language Generation Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou |
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Poster
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Tue 7:00 |
Variational Bayesian Quantization Yibo Yang, Robert Bamler, Stephan Mandt |
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Poster
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Tue 7:00 |
Amortized Population Gibbs Samplers with Neural Sufficient Statistics Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent |
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Poster
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Tue 8:00 |
Meta-learning for Mixed Linear Regression Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh |
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Poster
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Tue 9:00 |
Being Bayesian about Categorical Probability Taejong Joo, Uijung Chung, Min-Gwan Seo |
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Poster
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Tue 9:00 |
Variance Reduction in Stochastic Particle-Optimization Sampling Jianyi Zhang, Yang Zhao, Changyou Chen |
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Poster
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Tue 9:00 |
How Good is the Bayes Posterior in Deep Neural Networks Really? Florian Wenzel, Kevin Roth, Bastiaan Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin |
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Poster
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Tue 9:00 |
On Semi-parametric Inference for BART Veronika Rockova |
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Poster
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Tue 9:00 |
Source Separation with Deep Generative Priors Vivek Jayaram, John Thickstun |
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Poster
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Tue 10:00 |
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Schober, Philipp Hennig |
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Poster
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Tue 11:00 |
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse, Michael Gutmann |
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Poster
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Tue 11:00 |
Near-linear time Gaussian process optimization with adaptive batching and resparsification Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco |
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Poster
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Tue 12:00 |
On Contrastive Learning for Likelihood-free Inference Conor Durkan, Iain Murray, George Papamakarios |
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Poster
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Tue 13:00 |
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions Ahmed Alaa, Mihaela van der Schaar |
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Poster
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Tue 13:00 |
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans, Volodimir Begy, Gilles Louppe |
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Poster
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Tue 14:00 |
Thompson Sampling via Local Uncertainty Zhendong Wang, Mingyuan Zhou |
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Poster
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Tue 18:00 |
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama |
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Poster
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Wed 5:00 |
Robust Bayesian Classification Using An Optimistic Score Ratio Viet Anh Nguyen, Nian Si, Jose Blanchet |
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Poster
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Wed 5:00 |
Sequential Cooperative Bayesian Inference Junqi Wang, Pei Wang, Patrick Shafto |
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Poster
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Wed 5:00 |
Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations Stephen Keeley, David Zoltowski, Yiyi Yu, Spencer Smith, Jonathan Pillow |
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Poster
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Wed 5:00 |
Online Bayesian Moment Matching based SAT Solver Heuristics Haonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh |
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Poster
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Wed 8:00 |
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse Bin Dai, Ziyu Wang, David Wipf |
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Poster
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Wed 8:00 |
Undirected Graphical Models as Approximate Posteriors Arash Vahdat, Evgeny Andriyash, William Macready |
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Poster
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Wed 8:00 |
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck |
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Poster
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Wed 9:00 |
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong, Jimeng Sun, Chao Zhang |
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Poster
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Wed 9:00 |
Ordinal Non-negative Matrix Factorization for Recommendation Olivier Gouvert, Thomas Oberlin, Cedric Fevotte |
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Poster
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Wed 12:00 |
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel |
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Poster
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Wed 12:00 |
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support Yuan Zhou, Hongseok Yang, Yee-Whye Teh, Tom Rainforth |
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Poster
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Wed 12:00 |
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif |
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Poster
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Wed 12:00 |
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters Subho Banerjee, Saurabh Jha, Zbigniew Kalbarczyk, Ravishankar Iyer |
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Poster
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Wed 14:00 |
Healing Products of Gaussian Process Experts samuel cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Deisenroth |
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Poster
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Thu 6:00 |
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics Matt Hoffman, Yian Ma |
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Poster
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Thu 6:00 |
BINOCULARS for efficient, nonmyopic sequential experimental design Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett |
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Poster
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Thu 6:00 |
Causal Inference using Gaussian Processes with Structured Latent Confounders Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka |
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Poster
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Thu 8:00 |
Model Fusion with Kullback--Leibler Divergence Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon |
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Poster
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Thu 12:00 |
Inter-domain Deep Gaussian Processes Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal |
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Poster
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Thu 12:00 |
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks Jakub Swiatkowski, Kevin Roth, Bastiaan Veeling, Linh Tran, Josh V Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin |
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Poster
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Thu 13:00 |
Projective Preferential Bayesian Optimization Petrus Mikkola, Milica Todorović, Jari Järvi, Patrick Rinke, Samuel Kaski |
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Poster
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Thu 13:00 |
The Boomerang Sampler Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts |
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Poster
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Thu 15:00 |
Spectral Subsampling MCMC for Stationary Time Series Robert Salomone, Matias Quiroz, Robert kohn, Mattias Villani, Minh-Ngoc Tran |
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Poster
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Thu 17:00 |
Multi-objective Bayesian Optimization using Pareto-frontier Entropy Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama |