Variational Inference

Variance Reduction and Quasi-Newton for Particle-Based Variational Inference ICML 2020 Variational Autoencoders with Riemannian Brownian Motion Priors ICML 2020 Variational Bayesian Monte Carlo with Noisy Likelihoods NeurIPS 2020 Variational Bayesian Quantization ICML 2020 Variational Bayesian Unlearning NeurIPS 2020 Variational Inference for Sequential Data with Future Likelihood Estimates ICML 2020 Variational Inference for Sparse Gaussian Process Modulated Hawkes Process AAAI 2020 Variational Label Enhancement ICML 2020 Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge IJCAI 2020 Variational Metric Scaling for Metric-Based Meta-Learning AAAI 2020 Variational Neural Machine Translation with Normalizing Flows ACL 2020 Variational Pathway Reasoning for EEG Emotion Recognition AAAI 2020 VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition Modeling EMNLP 2020 Walsh-Hadamard Variational Inference for Bayesian Deep Learning NeurIPS 2020 A Generalization Bound for Online Variational Inference ACML 2019 Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing NeurIPS 2019 Amortized Bethe Free Energy Minimization for Learning MRFs NeurIPS 2019 A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization JMLR 2019 Augmenting and Tuning Knowledge Graph Embeddings UAI 2019 Automated Scalable Bayesian Inference via Hilbert Coresets JMLR 2019 Bayesian Posterior Approximation via Greedy Particle Optimization AAAI 2019 Block Neural Autoregressive Flow UAI 2019 Compound Probabilistic Context-Free Grammars for Grammar Induction ACL 2019 Dependency Grammar Induction with a Neural Variational Transition-Based Parser AAAI 2019 Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019