Probabilistic Modeling

Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective AAAI 2019 Evidence-based Trustworthiness ACL 2019 Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation AAAI 2019 Exact Gaussian Processes on a Million Data Points NeurIPS 2019 Expressive power of tensor-network factorizations for probabilistic modeling NeurIPS 2019 Face Alignment With Kernel Density Deep Neural Network ICCV 2019 Fast and Flexible Inference of Joint Distributions from their Marginals ICML 2019 Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay NeurIPS 2019 Faster Attend-Infer-Repeat with Tractable Probabilistic Models ICML 2019 Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs AAAI 2019 Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers ICLR 2019 Flexible Modeling of Diversity with Strongly Log-Concave Distributions NeurIPS 2019 Forward Amortized Inference for Likelihood-Free Variational Marginalization AISTATS 2019 Function-Space Distributions over Kernels NeurIPS 2019 Gaussian Process Latent Variable Alignment Learning AISTATS 2019 Gaussian Process Models of Sound Change in Indo-Aryan Dialectology ACL 2019 Gaussian Process Modulated Cox Processes under Linear Inequality Constraints AISTATS 2019 Generalized Boltzmann Machine with Deep Neural Structure AISTATS 2019 Generalized Maximum Entropy Estimation JMLR 2019 Generalizing the theory of cooperative inference AISTATS 2019 Generative Question Answering: Learning to Answer the Whole Question ICLR 2019 Generic Inference in Latent Gaussian Process Models JMLR 2019 Graph Convolutional Gaussian Processes ICML 2019 Graphical-model based estimation and inference for differential privacy ICML 2019 Harmonizable mixture kernels with variational Fourier features AISTATS 2019