amortized inference

Foundation Posteriors for Approximate Probabilistic Inference NeurIPS 2022 GATSBI: Generative Adversarial Training for Simulation-Based Inference ICLR 2022 Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders CVPR 2022 Generalization Gap in Amortized Inference NeurIPS 2022 Generative Flow Networks for Discrete Probabilistic Modeling ICML 2022 Group equivariant neural posterior estimation ICLR 2022 Langevin Autoencoders for Learning Deep Latent Variable Models NeurIPS 2022 Latent Time Neural Ordinary Differential Equations AAAI 2022 Learning Neural Set Functions Under the Optimal Subset Oracle NeurIPS 2022 Learning Not to Learn: Nature versus Nurture In Silico AAAI 2022 Neural Point Process for Learning Spatiotemporal Event Dynamics L4DC 2022 Neural Variational Dropout Processes ICLR 2022 Probabilistic surrogate networks for simulators with unbounded randomness UAI 2022 Structured Recognition for Generative Models with Explaining Away NeurIPS 2022 Training stochastic stabilized supralinear networks by dynamics-neutral growth NeurIPS 2022 Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification AISTATS 2021 Amortized Variational Inference for Simple Hierarchical Models NeurIPS 2021 Automatic variational inference with cascading flows ICML 2021 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design ICML 2021 Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations ICML 2021 Estimating Disentangled Belief about Hidden State and Hidden Task for Meta-Reinforcement Learning L4DC 2021 Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models ICLR 2021 NeRF-VAE: A Geometry Aware 3D Scene Generative Model ICML 2021 Nested Variational Inference NeurIPS 2021 Scalable Gaussian Process Variational Autoencoders AISTATS 2021