conftrace_

Artificial Intelligence

72,274 papers (0 classified directly here)

Subtopics

Core AI (59,089) Learning Paradigms (14,108) Bayesian & Probabilistic (4,335)

Papers per year

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Papers (including subtopics)

Structure Learning from Related Data Sets with a Hierarchical Bayesian Score PGM 2020
Tuning Causal Discovery Algorithms PGM 2020
Constraing-Based Learning for Continous-Time Bayesian Networks PGM 2020
Sum-Product Network Decompilation PGM 2020
Solving Multiple Inference by Minimizing Expected Loss PGM 2020
Supervised Learning with Background Knowledge PGM 2020
Bayesian network structure learning with causal effects in the presence of latent variables PGM 2020
Investigating Matureness of Probabilistic Graphical Models for Dry-Bulk Shipping PGM 2020
Lifted Query Answering in Gaussian Bayesian Networks PGM 2020
On a possibility of gradual model-learning PGM 2020
Causal Feature Learning for Utility-Maximizing Agents PGM 2020
Discovering cause-effect relationships in spatial systems with a known direction based on observational data PGM 2020
Correlated Equilibria for Approximate Variational Inference in MRFs PGM 2020
Learning Optimal Cyclic Causal Graphs from Interventional Data PGM 2020
Knowledge Transfer for Learning Markov Equivalence Classes PGM 2020
A New Perspective on Learning Context-Specific Independence PGM 2020
Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference PGM 2020
Building Causal Interaction Models by Recursive Unfolding PGM 2020
Hawkesian Graphical Event Models PGM 2020
Structural Causal Models Are (Solvable by) Credal Networks PGM 2020
CREDICI: A Java Library for Causal Inference by Credal Networks PGM 2020
CREMA: A Java Library for Credal Network Inference PGM 2020
A Software System for Predicting Patient Flow at the Emergency Department of Aalborg University Hospital PGM 2020
MeDIL: A Python Package for Causal Modelling PGM 2020
PGM_PyLib: A Toolkit for Probabilistic Graphical Models in Python PGM 2020