 Variational Autoencoders and Nonlinear ICA: A Unifying FrameworkInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 |
 Mixed-Variable Bayesian OptimizationInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 |
 Augmenting and Tuning Knowledge Graph EmbeddingsConference on Uncertainty in Artificial Intelligence (UAI), 2019 |
 The Thermodynamic Variational ObjectiveNeural Information Processing Systems (NeurIPS), 2019 |
 Divide and Couple: Using Monte Carlo Variational Objectives for
Posterior ApproximationNeural Information Processing Systems (NeurIPS), 2019 |
 Neural Topographic Factor Analysis for fMRI DataNeural Information Processing Systems (NeurIPS), 2019 Eli Sennesh Zulqarnain Khan Yiyu Wang Jennifer Dy Ajay B. Satpute J. B. Hutchinson Jan-Willem van de Meent |
 Amortized Bethe Free Energy Minimization for Learning MRFsNeural Information Processing Systems (NeurIPS), 2019 |
 Explicit Disentanglement of Appearance and Perspective in Generative
ModelsNeural Information Processing Systems (NeurIPS), 2019 |
 Neural Spline FlowsNeural Information Processing Systems (NeurIPS), 2019 |
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 Particle Filter Recurrent Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2019 |
 Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear
Dynamical SystemsInternational Conference on Machine Learning (ICML), 2019 |
 Practical and Consistent Estimation of f-DivergencesNeural Information Processing Systems (NeurIPS), 2019 |
 MaxEntropy Pursuit Variational InferenceInternational Symposium on Neural Networks (ISNN), 2019 |
 Deep Gaussian Processes with Importance-Weighted Variational InferenceInternational Conference on Machine Learning (ICML), 2019 |
 Correlated Variational Auto-EncodersInternational Conference on Machine Learning (ICML), 2019 |
 Learning Hierarchical Priors in VAEsNeural Information Processing Systems (NeurIPS), 2019 |
 Hierarchical Importance Weighted AutoencodersInternational Conference on Machine Learning (ICML), 2019 |
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 Importance Weighted Hierarchical Variational InferenceNeural Information Processing Systems (NeurIPS), 2019 Artem Sobolev Dmitry Vetrov |
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 Training Variational Autoencoders with Buffered Stochastic Variational
InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 |
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 Gaussian Mean Field Regularizes by Limiting Learned InformationEntropy (Entropy), 2019 |
