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Variational Inference

1946 directly classified papers

Papers per year

Papers

GumBolt: Extending Gumbel trick to Boltzmann priors NIPS 2018
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems NIPS 2018
Reparameterization Gradient for Non-differentiable Models NIPS 2018
Latent Alignment and Variational Attention NIPS 2018
Learning Disentangled Joint Continuous and Discrete Representations NIPS 2018
Orthogonally Decoupled Variational Gaussian Processes NIPS 2018
Using Large Ensembles of Control Variates for Variational Inference NIPS 2018
Point process latent variable models of larval zebrafish behavior NIPS 2018
GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model EMNLP 2018
Leveraging the Exact Likelihood of Deep Latent Variable Models NIPS 2018
A General Method for Amortizing Variational Filtering NIPS 2018
Provable Variational Inference for Constrained Log-Submodular Models NIPS 2018
Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction ACL 2017
Deep Quantization: Encoding Convolutional Activations With Deep Generative Model CVPR 2017
Infinite Variational Autoencoder for Semi-Supervised Learning CVPR 2017
Variational Inference for Sparse and Undirected Models ICML 2017
Deep Dynamic Poisson Factorization Model NIPS 2017
Variational Inference via $\chi$ Upper Bound Minimization NIPS 2017
Variational Memory Addressing in Generative Models NIPS 2017
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders NIPS 2017
Tag-Aware Personalized Recommendation Using a Hybrid Deep Model IJCAI 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference NIPS 2017
Context Selection for Embedding Models NIPS 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes NIPS 2017
Z-Forcing: Training Stochastic Recurrent Networks NIPS 2017