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Variational Inference

767 directly classified papers

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Papers

Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation ICML 2021
Monte Carlo Variational Auto-Encoders ICML 2021
Generalized Doubly Reparameterized Gradient Estimators ICML 2021
Composing Normalizing Flows for Inverse Problems ICML 2021
Automatic variational inference with cascading flows ICML 2021
A unified view of likelihood ratio and reparameterization gradients AISTATS 2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data AISTATS 2021
De-Confounded Variational Encoder-Decoder for Logical Table-to-Text Generation ACL 2021
Estimating High Order Gradients of the Data Distribution by Denoising NIPS 2021
Collapsed Variational Bounds for Bayesian Neural Networks NIPS 2021
Variational Continual Bayesian Meta-Learning NIPS 2021
Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation NIPS 2021
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization AAAI 2021
Continuous-time edge modelling using non-parametric point processes NIPS 2021
Challenging the Semi-Supervised VAE Framework for Text Classification EMNLP 2021
Generating Relevant and Coherent Dialogue Responses using Self-Separated Conditional Variational AutoEncoders ACL 2021
Probabilistic Transformer For Time Series Analysis NIPS 2021
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference IJCAI 2021
Spatio-Temporal Variational Gaussian Processes NIPS 2021
Coupled Gradient Estimators for Discrete Latent Variables NIPS 2021
VaB-AL: Incorporating Class Imbalance and Difficulty With Variational Bayes for Active Learning CVPR 2021
Variational Model-based Policy Optimization IJCAI 2021
Learning an Explicit Weighting Scheme for Adapting Complex HSI Noise CVPR 2021
Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification CVPR 2021