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Variational Inference

802 papers

Papers per year

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Papers

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021
On Variational Inference in Biclustering Models ICML 2021
On the difficulty of unbiased alpha divergence minimization ICML 2021
Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021
Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data ICML 2021
A Differentiable Point Process with Its Application to Spiking Neural Networks ICML 2021
Kernel Stein Discrepancy Descent ICML 2021
Bayesian Structural Adaptation for Continual Learning ICML 2021
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes ICML 2021
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification ICML 2021
Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders ICML 2021
Generative Particle Variational Inference via Estimation of Functional Gradients ICML 2021
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding ICML 2021
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes ICML 2021
Simple and Effective VAE Training with Calibrated Decoders ICML 2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition ICML 2021
Moreau-Yosida $f$-divergences ICML 2021
Monte Carlo Variational Auto-Encoders ICML 2021
Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021
Composing Normalizing Flows for Inverse Problems ICML 2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty ICML 2021
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference IJCAI 2021
Variational Model-based Policy Optimization IJCAI 2021