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Poster
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Tue 18:30
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An inner-loop free solution to inverse problems using deep neural networks
Kai Fan · Qi Wei · Lawrence Carin · Katherine Heller
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Poster
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Wed 18:30
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Convolutional Gaussian Processes
Mark van der Wilk · Carl Edward Rasmussen · James Hensman
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Poster
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Wed 18:30
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Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
Sergey Ioffe
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Poster
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Wed 18:30
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On Blackbox Backpropagation and Jacobian Sensing
Krzysztof Choromanski · Vikas Sindhwani
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Poster
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Mon 18:30
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The Reversible Residual Network: Backpropagation Without Storing Activations
Aidan Gomez · Mengye Ren · Raquel Urtasun · Roger Grosse
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Poster
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Tue 18:30
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Riemannian approach to batch normalization
Minhyung Cho · Jaehyung Lee
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Poster
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Tue 18:30
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Parallel Streaming Wasserstein Barycenters
Matt Staib · Sebastian Claici · Justin Solomon · Stefanie Jegelka
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Poster
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Tue 18:30
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Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks
Ziming Zhang · Matthew Brand
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Poster
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Mon 18:30
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Differentially private Bayesian learning on distributed data
Mikko Heikkilä · Eemil Lagerspetz · Samuel Kaski · Kana Shimizu · Sasu Tarkoma · Antti Honkela
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Poster
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Wed 18:30
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Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Geoffrey Roeder · Yuhuai Wu · David Duvenaud
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Poster
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Mon 18:30
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Tomography of the London Underground: a Scalable Model for Origin-Destination Data
Nicolò Colombo · Ricardo Silva · Soong Moon Kang
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Poster
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Wed 18:30
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PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Jonathan Huggins · Ryan Adams · Tamara Broderick
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