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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Learning Latent Semantic Annotations for Grounding Natural Language to Structured Data EMNLP 2018
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data NIPS 2018
Learning a latent manifold of odor representations from neural responses in piriform cortex NIPS 2018
Exponentiated Strongly Rayleigh Distributions NIPS 2018
Implicit Probabilistic Integrators for ODEs NIPS 2018
Importance Weighting and Variational Inference NIPS 2018
Provable Gaussian Embedding with One Observation NIPS 2018
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models NIPS 2018
Graphical model inference: Sequential Monte Carlo meets deterministic approximations NIPS 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models NIPS 2018
Scaling the Poisson GLM to massive neural datasets through polynomial approximations NIPS 2018
Nonparametric Density Estimation under Adversarial Losses NIPS 2018
Power-law efficient neural codes provide general link between perceptual bias and discriminability NIPS 2018
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes NIPS 2018
Overlapping Clustering Models, and One (class) SVM to Bind Them All NIPS 2018
Model-based targeted dimensionality reduction for neuronal population data NIPS 2018
Modeling Dynamic Missingness of Implicit Feedback for Recommendation NIPS 2018
Data-dependent PAC-Bayes priors via differential privacy NIPS 2018
Mallows Models for Top-k Lists NIPS 2018
Theoretical guarantees for EM under misspecified Gaussian mixture models NIPS 2018
Generalizing Tree Probability Estimation via Bayesian Networks NIPS 2018
Mental Sampling in Multimodal Representations NIPS 2018
Algebraic tests of general Gaussian latent tree models NIPS 2018
Lifted Weighted Mini-Bucket NIPS 2018
Deep Generative Markov State Models NIPS 2018