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Variational Inference

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TitleStatusHype
The equivalence between Stein variational gradient descent and black-box variational inference—0
CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection—0
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model CalibrationCode0
Markovian Score Climbing: Variational Inference with KL(p||q)—0
Deep Markov Spatio-Temporal FactorizationCode0
Variational Inference with Parameter Learning Applied to Vehicle Trajectory Estimation—0
Deep Reinforcement Learning with Weighted Q-Learning—0
Uncertainty Estimation in Cancer Survival Prediction—0
Nonparametric Deconvolution ModelsCode0
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data—0
Variational Inference for Deep Probabilistic Canonical Correlation Analysis—0
Learning Discrete State Abstractions With Deep Variational InferenceCode0
Towards Patient Record Summarization Through Joint Phenotype Learning in HIV Patients—0
Scalable Uncertainty for Computer Vision with Functional Variational Inference—0
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations—0
Automatic Differentiation Variational Inference with Mixtures—0
Bayesian Neural Networks With Maximum Mean Discrepancy RegularizationCode0
Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network—0
PlaNet of the Bayesians: Reconsidering and Improving Deep Planning Network by Incorporating Bayesian Inference—0
Stein Variational Inference for Discrete Distributions—0
MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference—0
Composing Normalizing Flows for Inverse Problems—0
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process ModelsCode0
Variational Inference and Bayesian CNNs for Uncertainty Estimation in Multi-Factorial Bone Age Prediction—0
Handling the Positive-Definite Constraint in the Bayesian Learning RuleCode0
Stochastic Normalizing Flows—0
Deep Gaussian Markov Random FieldsCode0
Large Scale Tensor Regression using Kernels and Variational Inference—0
Cross-modal variational inference for bijective signal-symbol translation—0
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations—0
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks—0
Gaussian Variational State Estimation for Nonlinear State-Space Models—0
Conditional Deep Gaussian Processes: multi-fidelity kernel learningCode0
Automatic structured variational inferenceCode0
An Equivalence between Bayesian Priors and Penalties in Variational Inference—0
On Implicit Regularization in β-VAEs—0
On the Information Bottleneck Problems: Models, Connections, Applications and Information Theoretic Views—0
Multivariate Gaussian Variational Inference by Natural Gradient Descent—0
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis—0
Newtonian Monte Carlo: single-site MCMC meets second-order gradient methodsCode0
CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric ModelsCode0
Lifted Hybrid Variational InferenceCode0
Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering—0
Variational Inference for Sequential Data with Future Likelihood Estimates—0
Efficient non-conjugate Gaussian process factor models for spike countdata using polynomial approximations—0
All in the (Exponential) Family: Information Geometry and Thermodynamic Variational Inference—0
On Implicit Regularization in -VAEs—0
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference—0
Variational Label Enhancement—0
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics—0
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