Papers
186 papers found
A Decision Support System to Predict Acute Fish Toxicity
Anders L Madsen, S. Jannicke Moe, Thomas Braunbeck et al.
A Hardware Perspective to Evaluating Probabilistic Circuits
Jelin Leslin, Antti Hyttinen, Karthekeyan Periasamy et al.
A Hybrid Algorithm for Learning Causal Networks using Uncertain Experts’ Knowledge
Christophe Gonzales, Axel Journe, Ahmed Mabrouk
Anytime Learning of Sum-Product and Sum-Product-Max Networks
Swaraj Pawar, Prashant Doshi
Approximate Inference for Stochastic Planning in Factored Spaces
Zhennan Wu, Roni Khardon
A Reparameterization of Mixtures of Truncated Basis Functions and its Applications
Antonio Salmerón, Helge Langseth, Andrés Masegosa et al.
A Transformational Characterization of Unconditionally Equivalent Bayesian Networks
Alex Markham, Danai Deligeorgaki, Pratik Misra et al.
Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling
Peter Strong, Jim Q. Smith
Bounding Counterfactuals under Selection Bias
Marco Zaffalon, Alessandro Antonucci, Rafael Cabañas et al.
Causal Discovery and Reinforcement Learning: A Synergistic Integration
Arquı́mides Méndez-Molina, Eduardo F.Morales, L. Enrique Sucar
Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models
Pierre Gillot, Pekka Parviainen
Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound
Kiattikun Chobtham, Anthony C. Constantinou
Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection
Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga
Explaining Deep Tractable Probabilistic Models: The sum-product network case
Bhagirath Athresh Karanam, Saurabh Mathur, Predrag Radivojac et al.
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models
Thijs van Ommen, Mathias Drton
Highly Efficient Structural Learning of Sparse Staged Trees
Manuele Leonelli, Gherardo Varando
Integrating Bayesian network classifiers to deal with the partial label ranking problem
Juan C. Alfaro, Juan A. Aledo, José A. Gámez
Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling
Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza
Knowledge transfer for learning subject-specific causal models
Verónica Rodrı́guez-López, Luis Enrique Sucar
Learning Noisy-Or Networks with an Application in Linguistics
František Kratochvíl, Václav Kratochvíl, Jiří Vomlel
Model inclusion lattice of coloured Gaussian graphical models for paired data
Alberto Roverato, Dung Ngoc Nguyen
Online Single-Microphone Source Separation using Non-Linear Autoregressive Models
Bart van Erp, Bert de Vries
Online Updating of Conditional Linear Gaussian Bayesian Networks
Anders L Madsen, Kristian G Olesen, Frank Jensen et al.
On the rank of 2×2×2 probability tables
Iván Pérez, Jiřı́ Vomlel