Variational Inference

Neural Relational Inference with Node-Specific Information ICLR 2022 On the detrimental effect of invariances in the likelihood for variational inference NeurIPS 2022 Para-CFlows: C^k-universal diffeomorphism approximators as superior neural surrogates NeurIPS 2022 Pathfinder: Parallel quasi-Newton variational inference JMLR 2022 Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks NeurIPS 2022 Probabilistic Implicit Scene Completion ICLR 2022 Reinforcement Learning in Presence of Discrete Markovian Context Evolution ICLR 2022 Rethinking Variational Inference for Probabilistic Programs with Stochastic Support NeurIPS 2022 Riemannian Diffusion Models NeurIPS 2022 Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods COLT 2022 Sampling with Mirrored Stein Operators ICLR 2022 The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders ICLR 2022 Variational oracle guiding for reinforcement learning ICLR 2022 A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models AISTATS 2021 Categorical Normalizing Flows via Continuous Transformations ICLR 2021 Contrastively Disentangled Sequential Variational Autoencoder NeurIPS 2021 DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks ACML 2021 Instance-Dependent Partial Label Learning NeurIPS 2021 Learning an Explicit Weighting Scheme for Adapting Complex HSI Noise CVPR 2021 Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation ACL 2021 Online Variational Filtering and Parameter Learning NeurIPS 2021 Quantifying Variational Approximation for Log-Partition Function COLT 2021 Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021 Scalable Bayesian Inverse Reinforcement Learning ICLR 2021 Treatment Effect Estimation with Disentangled Latent Factors AAAI 2021