Probabilistic Modeling

Correcting Predictions for Approximate Bayesian Inference AAAI 2020 CREMA: A Java Library for Credal Network Inference PGM 2020 DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks NeurIPS 2020 Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models ICML 2020 Data-dependent Gaussian Prior Objective for Language Generation ICLR 2020 Deep Bayesian Network for Visual Question Generation WACV 2020 Deep Gaussian Markov Random Fields ICML 2020 Deep Generalized Convolutional Sum-Product Networks PGM 2020 Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare AAAI 2020 Deep Sigma Point Processes UAI 2020 Design Adaptive AI for RTS Game by Learning Player's Build Order IJCAI 2020 Differentiable Algorithm for Marginalising Changepoints AAAI 2020 Discriminative Non-Parametric Learning of Arithmetic Circuits PGM 2020 Distortion estimates for approximate Bayesian inference UAI 2020 Diverse Image Captioning with Context-Object Split Latent Spaces NeurIPS 2020 Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support ICML 2020 Domain adaptation model for retinopathy detection from cross-domain OCT images MIDL 2020 Domain-Liftability of Relational Marginal Polytopes AISTATS 2020 Do sequence-to-sequence VAEs learn global features of sentences? EMNLP 2020 Double-Loop Unadjusted Langevin Algorithm ICML 2020 Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables ICML 2020 Dynamic content based ranking AISTATS 2020 Dynamic Control of Probabilistic Simple Temporal Networks AAAI 2020 Dynamic Embedding on Textual Networks via a Gaussian Process AAAI 2020 Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains NeurIPS 2020