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Variational Inference

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TitleStatusHype
Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds—0
BayesFormer: Transformer with Uncertainty Estimation—0
Longitudinal Deep Kernel Gaussian Process Regression—0
Learning Invariances using the Marginal Likelihood—0
Learning Hard Alignments with Variational Inference—0
An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process—0
Learning Generalizable Latent Representations for Novel Degradations in Super Resolution—0
Learning From Unpaired Data: A Variational Bayes Approach—0
Loss as the Inconsistency of a Probabilistic Dependency Graph: Choose Your Model, Not Your Loss Function—0
Deep kernel processes—0
Learning Model Reparametrizations: Implicit Variational Inference by Fitting MCMC distributions—0
Learning from demonstration using products of experts: applications to manipulation and task prioritization—0
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future—0
Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation—0
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning—0
Learning Distributions via Monte-Carlo Marginalization—0
Learning Distributions over Permutations and Rankings with Factorized Representations—0
Learning Optimal Filters Using Variational Inference—0
Learning proposals for sequential importance samplers using reinforced variational inference—0
Local-HDP: Interactive Open-Ended 3D Object Categorization in Real-Time Robotic Scenarios—0
Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems—0
Learning Set Functions with Implicit Differentiation—0
Deep Operator Networks for Bayesian Parameter Estimation in PDEs—0
Learning Deep Latent-variable MRFs with Amortized Bethe Free Energy Minimization—0
Local Expectation Gradients for Black Box Variational Inference—0
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