Variational Inference

Variational Information Bottleneck for Effective Low-Resource Fine-Tuning ICLR 2021 Variational Intrinsic Control Revisited ICLR 2021 Variational Pedestrian Detection CVPR 2021 Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization NeurIPS 2020 A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation COLING 2020 A Variational Approach for Learning from Positive and Unlabeled Data NeurIPS 2020 Capsule Routing via Variational Bayes AAAI 2020 Correlated Equilibria for Approximate Variational Inference in MRFs PGM 2020 Disentangled Representations for Sequence Data using Information Bottleneck Principle ACML 2020 f-Divergence Variational Inference NeurIPS 2020 Introducing Routing Uncertainty in Capsule Networks NeurIPS 2020 Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax NeurIPS 2020 Learning to Learn Variational Semantic Memory NeurIPS 2020 Localizing and Amortizing: Efficient Inference for Gaussian Processes ACML 2020 Markovian Score Climbing: Variational Inference with KL(p||q) NeurIPS 2020 Meta-Amortized Variational Inference and Learning AAAI 2020 NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations AAAI 2020 Probabilistic Circuits for Variational Inference in Discrete Graphical Models NeurIPS 2020 Probabilistic Graphical Models with Neural Networks in InferPy PGM 2020 Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS 2020 Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection ACML 2020 Scalable Uncertainty for Computer Vision With Functional Variational Inference CVPR 2020 Semi-supervised Parsing with a Variational Autoencoding Parser ACL 2020 Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models L4DC 2020 Structure Learning from Related Data Sets with a Hierarchical Bayesian Score PGM 2020