variational inference

PROVIDE: a probabilistic framework for unsupervised video decomposition UAI 2021 PSD Representations for Effective Probability Models NeurIPS 2021 q-Paths: Generalizing the geometric annealing path using power means UAI 2021 Quantifying Variational Approximation for Log-Partition Function COLT 2021 Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021 Randomized Automatic Differentiation ICLR 2021 Raven's Progressive Matrices Completion with Latent Gaussian Process Priors AAAI 2021 Recovering Latent Causal Factor for Generalization to Distributional Shifts NeurIPS 2021 Relative Variational Intrinsic Control AAAI 2021 Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space NeurIPS 2021 Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC AISTATS 2021 Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021 Scalable Bayesian GPFA with automatic relevance determination and discrete noise models NeurIPS 2021 Scalable Bayesian Inverse Reinforcement Learning ICLR 2021 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition ICML 2021 Scaling Gaussian Processes with Derivative Information Using Variational Inference NeurIPS 2021 Self-Adaptable Point Processes with Nonparametric Time Decays NeurIPS 2021 Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization AAAI 2021 Sequential core-set Monte Carlo UAI 2021 SHPOS: A Theoretical Guaranteed Accelerated Particle Optimization Sampling Method IJCAI 2021 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021 SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition NeurIPS 2021 Sliced Kernelized Stein Discrepancy ICLR 2021 Slice Sampling Reparameterization Gradients NeurIPS 2021 SoFA: Source-Data-Free Feature Alignment for Unsupervised Domain Adaptation WACV 2021