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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

An Algorithm to Learn Polytree Networks with Hidden Nodes NIPS 2019
The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA UAI 2019
Learning Nonsymmetric Determinantal Point Processes NIPS 2019
Flexible Modeling of Diversity with Strongly Log-Concave Distributions NIPS 2019
Statistical Model Aggregation via Parameter Matching NIPS 2019
Reachable Space Characterization of Markov Decision Processes with Time Variability RSS 2019
Recommendation from Raw Data with Adaptive Compound Poisson Factorization UAI 2019
Minimum Stein Discrepancy Estimators NIPS 2019
On Tractable Computation of Expected Predictions NIPS 2019
Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework EMNLP 2019
Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery EMNLP 2019
Evaluating Topic Quality with Posterior Variability EMNLP 2019
Expressive power of tensor-network factorizations for probabilistic modeling NIPS 2019
A Weighted Mini-Bucket Bound for Solving Influence Diagram UAI 2019
Identification In Missing Data Models Represented By Directed Acyclic Graphs UAI 2019
End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations UAI 2019
Belief Propagation: Accurate Marginals or Accurate Partition Function – Where is the Difference? UAI 2019
Approximate Causal Abstractions UAI 2019
Causal Discovery with General Non-Linear Relationships using Non-Linear ICA UAI 2019
Efficient Search-Based Weighted Model Integration UAI 2019
Comparing EM with GD in Mixture Models of Two Components UAI 2019
One-Shot Marginal MAP Inference in Markov Random Fields UAI 2019
Differentially Private Community Detection in Attributed Social Networks ACML 2019
Cross-sectional Learning of Extremal Dependence among Financial Assets NIPS 2019
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization NIPS 2019