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Probabilistic Modeling

2591 directly classified papers

Papers per year

Papers

Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning IJCAI 2017
Symbolic Priors for RNN-based Semantic Parsing IJCAI 2017
Unified Representation and Lifted Sampling for Generative Models of Social Networks IJCAI 2017
Bayesian Dynamic Mode Decomposition IJCAI 2017
A Density-based Nonparametric Model for Online Event Discovery from the Social Media Data IJCAI 2017
Improving Stochastic Block Models by Incorporating Power-Law Degree Characteristic IJCAI 2017
Coarse-to-Fine Lifted MAP Inference in Computer Vision IJCAI 2017
Zero-Inflated Exponential Family Embeddings ICML 2017
ChoiceRank: Identifying Preferences from Node Traffic in Networks ICML 2017
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier ICML 2017
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis ICML 2017
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling ICML 2017
An Infinite Hidden Markov Model With Similarity-Biased Transitions ICML 2017
Random Feature Expansions for Deep Gaussian Processes ICML 2017
On Relaxing Determinism in Arithmetic Circuits ICML 2017
Collapsed variational Bayes for Markov jump processes NIPS 2017
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models NIPS 2017
Inferring Generative Model Structure with Static Analysis NIPS 2017
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NIPS 2017
Targeting EEG/LFP Synchrony with Neural Nets NIPS 2017
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering NIPS 2017
Testing Bayesian Networks COLT 2017
Deep Dynamic Poisson Factorization Model NIPS 2017
Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting NIPS 2017
Filtering Variational Objectives NIPS 2017