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67 Results
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Oral
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Thu 12:00 |
Spectral Approximate Inference Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin |
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Poster
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Wed 18:30 |
The Variational Predictive Natural Gradient Da Tang · Rajesh Ranganath |
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Poster
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Thu 18:30 |
Spectral Approximate Inference Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin |
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Poster
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Tue 18:30 |
GMNN: Graph Markov Neural Networks Meng Qu · Yoshua Bengio · Jian Tang |
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Poster
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Tue 18:30 |
Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation Tahrima Rahman · Shasha Jin · Vibhav Gogate |
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Poster
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Tue 18:30 |
Inference and Sampling of -free Ising Models Valerii Likhosherstov · Yury Maximov · Misha Chertkov |
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Poster
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Thu 18:30 |
Variational Laplace Autoencoders Yookoon Park · Chris Kim · Gunhee Kim |
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Poster
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Tue 18:30 |
Understanding MCMC Dynamics as Flows on the Wasserstein Space Chang Liu · Jingwei Zhuo · Jun Zhu |
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Oral
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Tue 11:20 |
Calibrated Approximate Bayesian Inference Hanwen Xing · Geoff Nicholls · Jeong Lee |
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Poster
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Wed 18:30 |
Discovering Latent Covariance Structures for Multiple Time Series Anh Tong · Jaesik Choi |
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Poster
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Wed 18:30 |
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models Dilin Wang · Qiang Liu |
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Poster
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Thu 18:30 |
A Polynomial Time MCMC Method for Sampling from Continuous Determinantal Point Processes Alireza Rezaei · Shayan Oveis Gharan |