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Poster
Wed 12:45 Provable Hierarchical Imitation Learning via EM
Zhiyu Zhang · Ioannis Paschalidis
Poster
Wed 6:00 On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models
Yuyang Shi · Rob Cornish
Poster
Thu 7:30 Latent variable modeling with random features
Gregory Gundersen · Michael Zhang · Barbara Engelhardt
Poster
Thu 7:30 Variational Autoencoder with Learned Latent Structure
Marissa Connor · Gregory Canal · Christopher Rozell
Poster
Tue 14:00 Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
Mayee Chen · Benjamin Cohen-Wang · Stephen Mussmann · Frederic Sala · Christopher Re
Poster
Wed 12:45 Automatic Differentiation Variational Inference with Mixtures
Warren Morningstar · Sharad Vikram · Cusuh Ham · Andrew Gallagher · Joshua Dillon
Poster
Wed 6:00 Causal Autoregressive Flows
Ilyes Khemakhem · Ricardo Monti · Robert Leech · Aapo Hyvarinen
Poster
Wed 6:00 Scalable Gaussian Process Variational Autoencoders
Metod Jazbec · Matt Ashman · Vincent Fortuin · Michael Pearce · Stephan Mandt · Gunnar Rätsch
Poster
Tue 18:30 Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Frederik Kunstner · Raunak Kumar · Mark Schmidt
Poster
Wed 12:45 Geometrically Enriched Latent Spaces
Georgios Arvanitidis · Soren Hauberg · Bernhard Schölkopf
Poster
Tue 14:00 Learning GPLVM with arbitrary kernels using the unscented transformation
Daniel Augusto de Souza · Diego Mesquita · João Paulo Gomes · César Lincoln Mattos
Poster
Thu 7:30 Latent Gaussian process with composite likelihoods and numerical quadrature
Siddharth Ramchandran · Miika Koskinen · Harri Lähdesmäki