yusuke1997/dblp-id-title huggingface dataset:
KP4POI: Efficient POI Recommendation on Large-scale Datasets via Knowledge Prompting of Venues and Users
Hotel2vec: Learning Hotel Embeddings from User Click Sessions with Side Information
Proceedings of the Workshop on Recommenders in Tourism co-located with the 19th ACM Conference on Recommender Systems (RecSys 2025), Prague, Czech Republic, September 22, 2025
Structured Entity Extraction from Travel Videos Using Vision-Language Models
Multi-funnel Recommender System for Cold Item Boosting
TourWithMe: Recommending Peers to Visit Attractions Together
Predicting Your Next Trip: A Knowledge Graph-Based Multi-task Learning Approach for Travel Destination Recommendation
Proceedings of the Workshop on Recommenders in Tourism co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore and Online, September 19, 2023
Automatic Detection of Geotagged Food-Related Videos Using Aspect-Based Sentiment Analysis
Decision Support in Tourism through Social Robots: Design and Evaluation of a Conversation-Based Recommendation Approach Based on Tourist Segments
Balancing Preferences, Popularity and Location in Context-Aware Restaurant Deal Recommendation: A Bristol Case Study
A Framework for Recommender Systems Based on a Finite Multidimensional Model Space
A Simple Deep Personalized Recommendation System
TRACE: Transformer-based User Representations from Attributed Clickstream Event Sequences
Proceedings of the Workshop on Recommenders in Tourism co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019), Copenhagen, Denmark, September 19, 2019
Lifecycle of Promotional Campaigns in the Online Travel Industry
Accommodation Review Ranking for Tourism Recommendation
Cascaded Machine Learning Model for Efficient Hotel Recommendations from Air Travel Bookings
ProfileRec: Efficient Accommodation Review Ranking using Sentence Embeddings and Nearest-Neighbor Search
A Multimodal Dataset and Benchmark for Tourism Review Generation
Ski Resorts Recommendation using Deep Neural Networks
Event Recommendations through the Lens of Vision and Language Foundation Models
A Roadmap for Privacy Preserving Tourist Recommendation Systems
SMARTIE: Smart Museum for All Using a Range of Technology for Inclusive Experience
Extended Travel Itinerary Datasets Towards Reproducibility
Analysis of Relevant Factors in Online Hotel Recommendation Through Causal Models
BTRec: BERT-based Trajectory Recommendation for Personalized Tours
Local Sensitivity of Bayesian Networks to Multiple Simultaneous Parameter Shifts
Some Variations on the PC Algorithm
A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks
On Expressiveness of the AMP Chain Graph Interpretation
Mixture of Polynomials Probability Distributions for Grouped Sample Data
Literature Mining using Bayesian Networks
Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease
A Transformational Characterization of Unconditionally Equivalent Bayesian Networks
Bayesian Networks for Variable Groups
Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets
Serving MPE Queries on Tensor Networks by Computing Derivatives
A Differential Approach to Causality in Staged Trees
Recursive autonomy identification-based learning of augmented naive Bayes classifiers
The Dual PC Algorithm for Structure Learning
On the rank of 2×2×2 probability tables
Inhibited Effects in CP-Logic
Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks
GOBNILP: Learning Bayesian network structure with integer programming
Causal Discovery from Databases with Discrete and Continuous Variables
Representations of Bayesian networks by low-rank models
Counterfactually-Equivalent Structural Causal Modelling Using Causal Graphical Normalizing Flows
Consistent Estimation given Missing Data
Making Continuous Time Bayesian Networks More Flexible
Integrating Bayesian network classifiers to deal with the partial label ranking problem
Hawkesian Graphical Event Models
Geometry of rank tests
International Conference on Probabilistic Graphical Models, De Lindenberg, Nijmegen, the Netherlands, 11-13 September 2024
Bayesian Networks: a Combined Tuning Heuristic
Structural Causal Models Are (Solvable by) Credal Networks
Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity
The Parameterized Complexity of Approximate Inference in Bayesian Networks
International Conference on Probabilistic Graphical Models, PGM 2022, 5-7 October 2022, Almería, Spain
Estimation of linear, non-gaussian causal models in the presence of confounding latent variables
Hybrid Loopy Belief Propagation
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations
Predictive Maintenance using Dynamic Probabilistic Networks
A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations
Learning Acyclic Directed Mixed Graphs from Observations and Interventions
Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks
Gaussian Sum-Product Networks Learning in the Presence of Interval Censored Data
Finding Minimal Separators in LWF Chain Graphs
PGM_PyLib: A Toolkit for Probabilistic Graphical Models in Python
Enhancing Bayesian Networks with Psychometric Models
Dynamic importance sampling in Bayesian networks using factorisation of probability trees
Conditional Probability Estimation
Online Updating of Conditional Linear Gaussian Bayesian Networks
Structure Learning Under Missing Data
Causal Models, Value of Intervention, and Search for Opportunities
Simple Propagation with Arc-Reversal in Bayesian Networks
Bayesian Model Averaging of TAN Models for Clustering
Student Skill Models in Adaptive Testing
Learning Complex Bayesian Network Features for Classification
Causal Discovery and Reinforcement Learning: A Synergistic Integration
Multi-Label Classification with Cutset Networks
The Chordal Graph Polytope for Learning Decomposable Models
Investigating Matureness of Probabilistic Graphical Models for Dry-Bulk Shipping
Decision analysis with influence diagrams using Elvira's explanation facilities
Continuous Speech Recognition Using Dynamic Bayesian Networks. A Fast Decoding Algorithm
Learning Staged Trees from Incomplete Data
A Decision Support System to Predict Acute Fish Toxicity
A Bayesian Network Framework for the Construction of Virtual Agents with Human-like Behaviour
Sum-Product Network Decompilation
Reducing Propagation Effort in Large Polytrees: An Application to Information Retrieval
Learning Optimal Cyclic Causal Graphs from Interventional Data
Estimating Bounds on Causal Effects Considering Unmeasured Common Causes
Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks
A sum-product algorithm with polynomials for computing exact derivatives of the likelihood in Bayesian networks
Hybrid Copula Bayesian Networks
Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks
Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models
Approximate Solutions of Complex Influence Diagrams through MCMC Methods
Knowledge transfer for learning subject-specific causal models
Decisions and Dependence in Influence Diagrams
Uncovering Relationships using Bayesian Networks: A Case Study on Conspiracy Theories
Scalable Bayesian Network Structure Learning with Splines
Structural Sensitivity for the Knowledge Engineering of Bayesian Networks
Causal Feature Learning for Utility-Maximizing Agents
Formal Verification of Bayesian Network Classifiers
Continuous Decision MTE Influence Diagrams
An Efficient Low-Rank Tensors Representation for Algorithms in Complex Probabilistic Graphical Models
Constraing-Based Learning for Continous-Time Bayesian Networks
On Pruning with the MDL Score
Learning Parameters of Hybrid Time Bayesian Networks
Symmetric Causal Independence Models for Classification
A Pairwise Class Interaction Framework for Multilabel Classification
Compressing Bayes Net CPTs with Persistent Leaky Causes
Bayesian Torrent Classification by File Name and Size Only
Approximate Inference for Stochastic Planning in Factored Spaces
Learning Gated Bayesian Networks for Algorithmic Trading
On a possibility of gradual model-learning
Correlated Equilibria for Approximate Variational Inference in MRFs
Relevance for Robust Bayesian Network MAP-Explanations
Factorisation of Probability Trees and its Application to Inference in Bayesian Networks
Prediction of High Risk of Deviations in Home Care Deliveries
Learning decomposable models by coarsening
Dependency networks based classifiers: learning models by using independence
Exact learning augmented naive Bayes classifier
Extended Tree Augmented Naive Classifier
Preprocessing the MAP Problem
First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002 - Cuenca (Spain), Electronic Proceedings
Probabilistic Independence of Causal Influences
Learning Maximum Weighted (k+1)-Order Decomposable Graphs by Integer Linear Programming
The Independency tree model: a new approach for clustering and factorisation
Supervised Learning with Background Knowledge
Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials
Missing Values in Multiple Joint Inference of Gaussian Graphical Models
Learning Bayesian Networks by Branching on Constraints
Reintroducing Credal Networks under Epistemic Irrelevance
Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity
Causal Discovery from Subsampled Time Series Data by Constraint Optimization
An Exact Approach to Learning Probabilistic Relational Model
Computing Lower and Upper Bounds on the Probability of Causal Statements
Learning Bayesian Networks Structure using Markov Networks
Discrete model-based clustering with overlapping subsets of attributes
Fast Arc-Reversal
Inferentially Efficient Propagation in Non-Decomposable Bayesian Network with Hierarchical Junction Trees
Quartet-Based Learning of Shallow Latent Variables
Discovering cause-effect relationships in spatial systems with a known direction based on observational data
Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models
BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks
Online Algorithms for Sum-Product Networks with Continuous Variables
An Extended MPL-C Model for Bayesian Network Parameter Learning with Exterior Constraints
A Progressive Explanation of Inference in 'Hybrid' Bayesian Networks for Supporting Clinical Decision Making
MeDIL: A Python Package for Causal Modelling
Optimal Design with Design Networks
On the Unlikelihood of D-Separation
Multicausal Prior Families, Randomisation and Essential Graphs
Building Causal Interaction Models by Recursive Unfolding
On Stacking Probabilistic Temporal Models with Bidirectional Information Flow
Finding Optimal Bayesian Networks with Local Structure
A Novel Approach to Handle Inference in Discrete Markov Networks with Large Label Sets
Parallel Probabilistic Inference by Weighted Model Counting
Dual Formulation of the Chordal Graph Conjecture
Deep Generalized Convolutional Sum-Product Networks
Trading off Speed and Accuracy in Multilabel Classification
New Structures for Conditional Probability Tables
Learning Tractable Multidimensional Bayesian Network Classifiers
Knowledge Transfer for Learning Markov Equivalence Classes
Sensitivity analysis of extreme inaccuracies in Gaussian Bayesian Networks
Cauchy Graphical Models
Interactive Anomaly Detection in Mixed Tabular Data using Bayesian Networks
Markov Random Field MAP as Set Partitioning
Evaluating Causal effects using Chain Event Graphs
Treewidth and the Computational Complexity of MAP Approximations
Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks
Bayesian Networks in Educational Testing
Naive Bayesian Classifiers with Extreme Probability Features
ρ-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows
Lattices for Studying Monotonicity of Bayesian Networks
Online Single-Microphone Source Separation using Non-Linear Autoregressive Models
Probabilistic Graphical Models with Neural Networks in InferPy
Bayesian network structure learning with causal effects in the presence of latent variables
Circular Chain Classifiers
A Software System for Predicting Patient Flow at the Emergency Department of Aalborg University Hospital
aGrUM/pyAgrum : a toolbox to build models and algorithms for Probabilistic Graphical Models in Python
Who did it? Identifying the Most Likely Origins of Events
Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms
Hierarchical Dependency Constrained Averaged One-Dependence Estimators Classifiers for Hierarchical Feature Spaces
Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers
Hugin - The Tool for Bayesian Networks and Influence Diagrams
A Hybrid Algorithm for Learning Causal Networks using Uncertain Experts' Knowledge
The Functional LiNGAM
Q-conjugate Message Passing for Efficient Bayesian Inference
Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity
International Conference on Probabilistic Graphical Models, PGM 2020, 23-25 September 2020, Aalborg, Hotel Comwell Rebild Bakker, Skørping, Denmark
Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study
Probabilistic Graphical Models - Eighth International Conference, PGM 2016, Lugano, Switzerland, September 6-9, 2016. Proceedings
Robustifying the Viterbi Algorithm
Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures
Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling
An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical Models
Scaled Conjugate Gradients for Maximum Likelihood: An Empirical Comparison with the EM Algorithm
An Order-based Algorithm for Learning Structure of Bayesian Networks
International Conference on Probabilistic Graphical Models, PGM 2018, 11-14 September 2018, Prague, Czech Republic
Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery
AutoCD: Automated Machine Learning for Causal Discovery Algorithms
Evidence Evaluation: a Study of Likelihoods and Independence
Time-Approximation Trade-Offs for Learning Bayesian Networks
Multi-label Classification for Tree and Directed Acyclic Graphs Hierarchies
Ψnet: Efficient Causal Modeling at Scale
Limited Memory Influence Diagrams for Attribute Statistical Process Control with Variable Sample Sizes
An Adaptive Implicit Hitting Set Algorithm for MAP and MPE Inference
Learning Parameters in Canonical Models Using Weighted Least Squares
Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection
A Short Note on Discrete Representability of Independence Models
Discrete Bayesian Network Interpretation of the Cox's Proportional Hazards Model
An Empirical Study of Methods for SPN Learning and Inference
Parameterized hardness of active inference
A Lattice Representation of Independence Relations
Supervised Classification Using Hybrid Probabilistic Decision Graphs
A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization
Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks
Minimizing Relative Entropy in Hierarchical Predictive Coding
Evaluation of Rules for Coping with Insufficient Data in Constraint-Based Search Algorithms
Context-Specific Refinements of Bayesian Network Classifiers
Exploring Argument Mining and Bayesian Networks for Assessing Topics for City Project Proposals
Bayesian Network Model Averaging Classifiers by Subbagging
Eliminating Variable Order Instability in Greedy Score-Based Structure Learning
Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification
A Hardware Perspective to Evaluating Probabilistic Circuits
From Information to Evidence in a Bayesian Network
Evidence and Scenario Sensitivities in Naive Bayesian Classifiers
Cooperative Verification of Agent Interface
Kernel-based Approach for Learning Causal Graphs from Mixed Data
Same-Decision Probability: Threshold Robustness and Application to Explanation
Selecting Strategies for Infinite-Horizon Dynamic LIMIDS
Speeding Up k-Neighborhood Local Search in Limited Memory Influence Diagrams
Learning Bayesian Network Structures When Discrete and Continuous Variables Are Present
Approximating bounded tree-width Bayesian network classifiers with OBDD
Handling of Deterministic Relationships in Constraint-based Causal Discovery
Probabilistic Graphical Models - 7th European Workshop, PGM 2014, Utrecht, The Netherlands, September 17-19, 2014. Proceedings
Forward-Backward Splitting for Time-Varying Graphical Models
Structure Learning from Related Data Sets with a Hierarchical Bayesian Score
Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences
Cascading Sum-Product Networks using Robustness
Statistical Matching of Discrete Data by Bayesian Networks
Restricted Bayesian Network Structure Learning
Parameterized Completeness Results for Bayesian Inference
Poset Representations for Sets of Elementary Triplets
Differentiable TAN Structure Learning for Bayesian Network Classifiers
Latent Gaussian Graphical Models with Golazo Penalty
Learning Essential Graph Markov Models From Data
Efficient Detection of Commutative Factors in Factor Graphs
CREDICI: A Java Library for Causal Inference by Credal Networks
Lifted Query Answering in Gaussian Bayesian Networks
Learning Causal Markov Boundaries with Mixed Observational and Experimental Data
Alternative Measures of Direct and Indirect Effects
Adapting Bayes Network Structures to Non-stationary Domains
Making Large Cox's Proportional Hazard Models Tractable in Bayesian Networks
Identifying the irreducible disjoint factors of a multivariate probability distribution
Constructing a Chain Event Graph from a Staged Tree
Highly Efficient Structural Learning of Sparse Staged Trees
Graphical Models to Causal Discovery from Data
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models
Sparse Learning in Gaussian Chain Graphs for State Space Models
Estimating Mixtures of Truncated Exponentials from Data
A partial orthogonalization method for simulating covariance and concentration graph matrices
Geometric No-U-Turn Samplers: Concepts and Evaluation
Solving M-Modes in Loopy Graphs Using Tree Decompositions
Complexity Results for Enhanced Qualitative Probabilistic Networks
On the Relative Expressiveness of Bayesian and Neural Networks
Tuning Causal Discovery Algorithms
Who Learns Better Bayesian Network Structures: Constraint-Based, Score-based or Hybrid Algorithms?
Balancing Computational Cost and Accuracy in Inference of Continuous Bayesian Networks
An Extension of Lazy Evaluation for Influence Diagrams Avoiding Redundant Variables in the Potentials
Towards a Bayesian Decision Theoretic Analysis of Contextual Effect Modifiers
Estimating Causal Effects with Ancestral Graph Markov Models
Residual Sum-Product Networks
Proceedings of the 9th International Conference on Probabilistic Graphical Models
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach
Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks
Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data
Anytime Learning of Sum-Product and Sum-Product-Max Networks
Discriminative Non-Parametric Learning of Arithmetic Circuits
Causal Structure Learning With Momentum: Sampling Distributions Over Markov Equivalence Classes
Abstraction and Refinement for Solving Continuous Markov Decision Processes
Third European Workshop on Probabilistic Graphical Models, 12-15 September 2006, Prague, Czech Republic. Electronic Proceedings
Almost No News on the Complexity of MAP in Bayesian Networks
Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference
Dynamic Sum Product Networks for Tractable Inference on Sequence Data
Soft Learning Probabilistic Circuits
Robust Estimation of Laplacian Constrained Gaussian Graphical Models with Trimmed Non-convex Regularization
A Divide and Conquer Approach for Solving Structural Causal Models
Elvira: An Environment for Creating and Using Probabilistic Graphical Models
Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets
Learning Optimal Causal Graphs with Exact Search
An Empirical-Bayes Score for Discrete Bayesian Networks
On SPI-Lazy Evaluation of Influence Diagrams
A Hybrid Causal Search Algorithm for Latent Variable Models
Modelling Shared Decision Making Interactions using Influence Diagrams
Contrastive Divergence Learning with Chained Belief Propagation
LIMID Quality Control Models for Increasing Failure Rate Processes
Learning Semi-Markovian Causal Models using Experiments
On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification
Diagnosing Lyme disease - Tailoring patient specific Bayesian networks for temporal reasoning
Causal Structure Learning via Temporal Markov Networks
Speeding up approximate MAP by applying domain knowledge about relevant variables
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks
Lifted Weight Learning of Markov Logic Networks (Revisited One More Time)
CREMA: A Java Library for Credal Network Inference
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks
Learning Noisy-Or Networks with an Application in Linguistics
Bayesian Network Structure Learning with Side Constraints
Estimating Mutual Information in Under-Reported Variables
Learning Bayesian network classifiers with completed partially directed acyclic graphs
Regime Aware Learning
A Study of Recently Discovered Equalities about Latent Tree Models Using Inverse Edges
Loopy Propagation: the Convergence Error in Markov Networks
Privacy Sensitive Construction of Junction Tree Agent Organization for Multiagent Graphical Models
A Reparameterization of Mixtures of Truncated Basis Functions and its Applications
Efficient Heuristic Search for M-Modes Inference
Bayesian Network Classifiers Under the Ensemble Perspective
Discriminative Training of Sum-Product Networks by Extended Baum-Welch
Learning Marginal AMP Chain Graphs under Faithfulness
Explaining Deep Tractable Probabilistic Models: The sum-product network case
Floating Search Methods in Learning Bayesian Networks
Bayesian Network Inference Using Marginal Trees
Differential networking with path weights in Gaussian trees
Multi-dimensional Bayesian Network Classifiers
A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs
On Bayesian Network Inference with Simple Propagation
Causal Independence Models for Continuous Time Bayesian Networks
Intervals of Causal Effects for Learning Causal Graphical Models
Logical Hidden Markov Models (Extendes abstract)
Bounding Counterfactuals under Selection Bias
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case
Equivalences between Maximum a Posteriori Inference in Bayesian Networks and Maximum Expected Utility Computation in Influence Diagrams
Extended Probability Trees for Probabilistic Graphical Models
Probabilistic Decision Graphs - Combining Verification and AI Techniques for Probabilistic Inference
Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models
Learning Non-parametric Markov Networks with Mutual Information
Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph
Bayesian Networks with Function Nodes
Compression of Bayesian Networks with NIN-AND Tree Modeling
Solving Multiple Inference by Minimizing Expected Loss
Locally specified credal networks
Structure Learning for Bayesian Networks over Labeled DAGs
d-VMP: Distributed Variational Message Passing
Instance-Specific Bayesian Network Structure Learning