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Variational Inference

802 papers

Papers per year

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Papers

Complex-Valued Variational Autoencoder: A Novel Deep Generative Model for Direct Representation of Complex Spectra INTERSPEECH 2020
Stochastic Convolutional Recurrent Networks for Language Modeling INTERSPEECH 2020
Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators JMLR 2020
Bayesian joint state and parameter tracking in autoregressive models L4DC 2020
Probabilistic Graphical Models with Neural Networks in InferPy PGM 2020
Amortized variance reduction for doubly stochastic objective UAI 2020
Deep Sigma Point Processes UAI 2020
Universal Boosting Variational Inference NIPS 2019
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series NIPS 2019
Stein Variational Gradient Descent With Matrix-Valued Kernels NIPS 2019
Multi-task Learning for Aggregated Data using Gaussian Processes NIPS 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices NIPS 2019
Learning Hierarchical Priors in VAEs NIPS 2019
Learning Hawkes Processes from a handful of events NIPS 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods NIPS 2019
Learning Disentangled Representations for Recommendation NIPS 2019
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing NIPS 2019
Tensor Monte Carlo: Particle Methods for the GPU era NIPS 2019
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NIPS 2019
Amortized Bethe Free Energy Minimization for Learning MRFs NIPS 2019
Variational Bayes under Model Misspecification NIPS 2019
The continuous Bernoulli: fixing a pervasive error in variational autoencoders NIPS 2019
Variational Inference MPC for Bayesian Model-based Reinforcement Learning CORL 2019
Hyperprior Induced Unsupervised Disentanglement of Latent Representations AAAI 2019
Bayesian Posterior Approximation via Greedy Particle Optimization AAAI 2019