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Variational Inference

767 directly classified papers

Papers per year

Papers

Reparameterizing Distributions on Lie Groups AISTATS 2019
Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation EMNLP 2019
uniblock: Scoring and Filtering Corpus with Unicode Block Information EMNLP 2019
Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model CVPR 2019
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow UAI 2019
Variational Inference of Penalized Regression with Submodular Functions UAI 2019
Topic Modeling with Wasserstein Autoencoders ACL 2019
The LORACs Prior for VAEs: Letting the Trees Speak for the Data AISTATS 2019
The continuous Bernoulli: fixing a pervasive error in variational autoencoders NIPS 2019
Variational Bayes under Model Misspecification NIPS 2019
Hyperprior Induced Unsupervised Disentanglement of Latent Representations AAAI 2019
Multi-Source Neural Variational Inference AAAI 2019
Learning Disentangled Representation with Pairwise Independence AAAI 2019
Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation AAAI 2019
Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts AAAI 2019
Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019
Amortized Bethe Free Energy Minimization for Learning MRFs NIPS 2019
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NIPS 2019
Tensor Monte Carlo: Particle Methods for the GPU era NIPS 2019
Learning Disentangled Representations for Recommendation NIPS 2019
Block Neural Autoregressive Flow UAI 2019
Enhancing Variational Autoencoders with Mutual Information Neural Estimation for Text Generation IJCNLP 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods NIPS 2019
Learning Hawkes Processes from a handful of events NIPS 2019
Learning Hierarchical Priors in VAEs NIPS 2019