| A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis | Jan 22, 2020 | Computational EfficiencyVariational Inference | —Unverified | 0 |
| Newtonian Monte Carlo: single-site MCMC meets second-order gradient methods | Jan 15, 2020 | Second-order methodsVariational Inference | CodeCode Available | 0 |
| CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric Models | Jan 13, 2020 | ClusteringTopic Models | CodeCode Available | 0 |
| Lifted Hybrid Variational Inference | Jan 8, 2020 | Variational Inference | CodeCode Available | 0 |
| Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering | Jan 7, 2020 | ClusteringMissing Values | —Unverified | 0 |
| Scalable Gradients for Stochastic Differential Equations | Jan 5, 2020 | SensitivityVariational Inference | CodeCode Available | 2 |
| All in the (Exponential) Family: Information Geometry and Thermodynamic Variational Inference | Jan 1, 2020 | AllScheduling | —Unverified | 0 |
| Variational Inference for Sequential Data with Future Likelihood Estimates | Jan 1, 2020 | Variational Inference | —Unverified | 0 |
| On Implicit Regularization in -VAEs | Jan 1, 2020 | Variational Inference | —Unverified | 0 |
| Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics | Jan 1, 2020 | Variational Inference | —Unverified | 0 |
| Variational Label Enhancement | Jan 1, 2020 | Multi-Label LearningVariational Inference | —Unverified | 0 |
| Efficient non-conjugate Gaussian process factor models for spike countdata using polynomial approximations | Jan 1, 2020 | Variational Inference | —Unverified | 0 |
| Variance Reduction and Quasi-Newton for Particle-Based Variational Inference | Jan 1, 2020 | Bayesian InferenceRiemannian optimization | —Unverified | 0 |
| Approximate Inference for Fully Bayesian Gaussian Process Regression | Dec 31, 2019 | GPRregression | CodeCode Available | 0 |
| Hierarchical Variational Imitation Learning of Control Programs | Dec 29, 2019 | Imitation LearningVariational Inference | CodeCode Available | 0 |
| End-to-End Pixel-Based Deep Active Inference for Body Perception and Action | Dec 28, 2019 | Variational Inference | CodeCode Available | 0 |
| Variational Metric Scaling for Metric-Based Meta-Learning | Dec 26, 2019 | Few-Shot LearningMeta-Learning | CodeCode Available | 0 |
| Mixture of Inference Networks for VAE-based Audio-visual Speech Enhancement | Dec 23, 2019 | DecoderSpeech Enhancement | —Unverified | 0 |
| Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines | Dec 23, 2019 | Compressive SensingComputational Efficiency | —Unverified | 0 |
| Pseudo-Encoded Stochastic Variational Inference | Dec 19, 2019 | DecoderVariational Inference | —Unverified | 0 |
| A Closer Look at Disentangling in β-VAE | Dec 11, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Frequentist Consistency of Generalized Variational Inference | Dec 10, 2019 | Variational Inference | —Unverified | 0 |
| Solving Bayesian Inverse Problems via Variational Autoencoders | Dec 5, 2019 | Uncertainty QuantificationVariational Inference | —Unverified | 0 |
| Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression | Dec 5, 2019 | regressionStochastic Optimization | —Unverified | 0 |
| Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning | Dec 4, 2019 | Continual LearningVariational Inference | —Unverified | 0 |
