David Poole

ORCID

Publication Activity (10 Years)

Years Active: 1984-2023
Publications (10 Years): 33

Top Venues

CoRR

AAAI Workshop: Statistical Relational Artificial Intelligence

AAAI

Publications

Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole
Knowledge Hypergraph Embedding Meets Relational Algebra. J. Mach. Learn. Res. 24 (2023)
Matthew Dirks, David Poole
Auto-Encoder Neural Network Incorporating X-Ray Fluorescence Fundamental Parameters with Machine Learning. CoRR (2022)
Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahareh Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan
Structure learning for relational logistic regression: an ensemble approach. Data Min. Knowl. Discov. 35 (5) (2021)
Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole
Knowledge Hypergraph Embedding Meets Relational Algebra. CoRR (2021)
Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole
Knowledge Hypergraphs: Prediction Beyond Binary Relations. IJCAI (2020)
Matthew C. Dirks, David Poole
Binarised Regression with Instance-Varying Costs: Evaluation using Impact Curves. CoRR (2020)
Ainaz Hajimoradlou, Gioachino Roberti, David Poole
Predicting Landslides Using Locally Aligned Convolutional Neural Networks. IJCAI (2020)
Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole
Knowledge Hypergraphs: Extending Knowledge Graphs Beyond Binary Relations. CoRR (2019)
Bahare Fatemi, Siamak Ravanbakhsh, David Poole
Improved Knowledge Graph Embedding Using Background Taxonomic Information. AAAI (2019)
Ainaz Hajimoradlou, Gioachino Roberti, David Poole
A Probabilistic Approach for Predicting Landslides by Learning a Self-Aligned Deep Convolutional Model. CoRR (2019)
Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR (2018)
Bahare Fatemi, Siamak Ravanbakhsh, David Poole
Improved Knowledge Graph Embedding using Background Taxonomic Information. CoRR (2018)
Seyed Mehran Kazemi, David Poole
SimplE Embedding for Link Prediction in Knowledge Graphs. CoRR (2018)
Sanjana Bajracharya, Giuseppe Carenini, Brent C. Chamberlain, Kai Di Chen, Daniel Klein, David Poole, Hamed Taheri, Gunilla Öberg
Interactive Visualization for Group Decision Analysis. Int. J. Inf. Technol. Decis. Mak. 17 (6) (2018)
Seyed Mehran Kazemi, David Poole
RelNN: A Deep Neural Model for Relational Learning. AAAI (2018)
Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan
Structure Learning for Relational Logistic Regression: An Ensemble Approach. CoRR (2018)
Seyed Mehran Kazemi, David Poole
SimplE Embedding for Link Prediction in Knowledge Graphs. NeurIPS (2018)
Seyed Mehran Kazemi, David Poole
Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models. Frontiers Robotics AI 5 (2018)
Bahare Fatemi, Seyed Mehran Kazemi, David Poole
Record Linkage to Match Customer Names: A Probabilistic Approach. CoRR (2018)
Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole
Domain Recursion for Lifted Inference with Existential Quantifiers. CoRR (2017)
David Buchman, David Poole
Negative probabilities in probabilistic logic programs. Int. J. Approx. Reason. 83 (2017)
Seyed Mehran Kazemi, David Poole
RelNN: A Deep Neural Model for Relational Learning. CoRR (2017)
Seyed Mehran Kazemi, Bahare Fatemi, Alexandra Kim, Zilun Peng, Moumita Roy Tora, Xing Zeng, Matthew C. Dirks, David Poole
Comparing Aggregators for Relational Probabilistic Models. CoRR (2017)
David Buchman, David Poole
Why Rules are Complex: Real-Valued Probabilistic Logic Programs are not Fully Expressive. UAI (2017)
Bahare Fatemi, Seyed Mehran Kazemi, David Poole
A Learning Algorithm for Relational Logistic Regression: Preliminary Results. CoRR (2016)
Thomas Lukasiewicz, Maria Vanina Martinez, David Poole, Gerardo Ignacio Simari
Probabilistic Models over Weighted Orderings: Fixed-Parameter Tractable Variable Elimination. KR (2016)
Matthew C. Dirks, Andrew Csinger, Andrew Bamber, David Poole
Representation, Reasoning, and Learning for a Relational Influence Diagram Applied to a Real-Time Geological Domain. Canadian Conference on AI (2016)
Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole
New Liftable Classes for First-Order Probabilistic Inference. NIPS (2016)
Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole
New Liftable Classes for First-Order Probabilistic Inference. CoRR (2016)
Seyed Mehran Kazemi, David Poole
Lazy Arithmetic Circuits. AAAI Workshop: Beyond NP (2016)
Seyed Mehran Kazemi, David Poole
Knowledge Compilation for Lifted Probabilistic Inference: Compiling to a Low-Level Language. KR (2016)
Seyed Mehran Kazemi, David Poole
Why is Compiling Lifted Inference into a Low-Level Language so Effective? CoRR (2016)
David Buchman, David Poole
Negation Without Negation in Probabilistic Logic Programming. KR (2016)
Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36 (1) (2015)
David Buchman, David Poole
Representing Aggregators in Relational Probabilistic Models. AAAI (2015)
Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole
Relational Logistic Regression. KR (2014)
Seyed Mehran Kazemi, David Poole
Elimination Ordering in Lifted First-Order Probabilistic Inference. AAAI (2014)
Matthew C. Dirks, Andrew Csinger, Andrew Bamber, David Poole
Representation, Reasoning, and Learning for a Relational Influence Diagram Applied to a Real-Time Geological Domain. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
David Poole, David Buchman, Seyed Mehran Kazemi, Kristian Kersting, Sriraam Natarajan
Population Size Extrapolation in Relational Probabilistic Modelling. SUM (2014)
Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, David Poole
Preface. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Brent C. Chamberlain, Giuseppe Carenini, Gunilla Öberg, David Poole, Hamed Taheri
A Decision Support System for the Design and Evaluation of Sustainable Wastewater Solutions. IEEE Trans. Computers 63 (1) (2014)
Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole
Relational Logistic Regression: The Directed Analog of Markov Logic Networks. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Rita Sharma, David Poole
Symmetric Collaborative Filtering Using the Noisy Sensor Model CoRR (2013)
Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Hai Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Dimitri Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar
The AAAI-13 Conference Workshops. AI Mag. 34 (4) (2013)
Ramón López de Mántaras, David Poole
Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (1994) CoRR (2013)
David Poole
Foundations of model construction in feature-based semantic science. J. Log. Comput. 23 (5) (2013)
Chia-Li Kuo, David Buchman, Arzoo Katiyar, David Poole
Probabilistic Reasoning with Undefined Properties in Ontologically-Based Belief Networks. IJCAI (2013)
Peter Gorniak, David Poole
Building a Stochastic Dynamic Model of Application Use CoRR (2013)
Craig Boutilier, Ronen I. Brafman, Holger H. Hoos, David Poole
Reasoning With Conditional Ceteris Paribus Preference Statem CoRR (2013)
Chia-Li Kuo, David Poole
On Integrating Ontologies with Relational Probabilistic Models. AAAI Workshop: Statistical Relational Artificial Intelligence (2013)
Vibhav Gogate, Kristian Kersting, Sriraam Natarajan, David Poole
Preface. AAAI Workshop: Statistical Relational Artificial Intelligence (2013)
David Poole, Mark Crowley
Cyclic Causal Models with Discrete Variables: Markov Chain Equilibrium Semantics and Sample Ordering. IJCAI (2013)
Michael Chiang, David Poole
Reference classes and relational learning. Int. J. Approx. Reason. 53 (3) (2012)
Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole
Nonparametric Bayesian Logic CoRR (2012)
Jacek Kisynski, David Poole
Constraint Processing in Lifted Probabilistic Inference CoRR (2012)
David Poole, David Buchman, Sriraam Natarajan, Kristian Kersting
Aggregation and Population Growth: The Relational Logistic Regression and Markov Logic Cases. StarAI@UAI (2012)
Mark Crowley, John Nelson, David Poole
Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making CoRR (2012)
David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando de Freitas
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models. AISTATS (2012)
Stephen Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan
ILP turns 20 - Biography and future challenges. Mach. Learn. 86 (1) (2012)
Rita Sharma, David Poole
Efficient Inference in Large Discrete Domains CoRR (2012)
Michael Chiang, David Poole
A Search Algorithm for Latent Variable Models with Unbounded Domains. AAAI (2012)
David Poole, Fahiem Bacchus, Jacek Kisynski
Towards Completely Lifted Search-based Probabilistic Inference CoRR (2011)
David Poole
Logic, Probability and Computation: Foundations and Issues of Statistical Relational AI. LPNMR (2011)
Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, David Poole
CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements CoRR (2011)
Mark Crowley, David Poole
Policy Gradient Planning for Environmental Decision Making with Existing Simulators. AAAI (2011)
Rita Sharma, David Poole, Clinton Smyth
A framework for ontologically-grounded probabilistic matching. Int. J. Approx. Reason. 51 (2) (2010)
David Poole
Probabilistic Relational Learning and Inductive Logic Programming at a Global Scale. ILP (2010)
David Poole
Towards a Logic of Feature-Based Semantic Science Theories. KR (2010)
Todd W. Neller, John DeNero, Dan Klein, Sven Koenig, William Yeoh, Xiaoming Zheng, Kenny Daniel, Alex Nash, Zachary Dodds, Giuseppe Carenini, David Poole, Christopher Brooks
Model AI Assignments. EAAI (2010)
Jacek Kisynski, David Poole
Constraint Processing in Lifted Probabilistic Inference. UAI (2009)
Mark LaRosa, David Poole, Rudy Schusteritsch
Designing and deploying usetube, google's global user experience observation and recording system. CHI Extended Abstracts (2009)
Jacek Kisynski, David Poole
Lifted Aggregation in Directed First-Order Probabilistic Models. IJCAI (2009)
David Poole, Clinton Smyth, Rita Sharma
Ontology Design for Scientific Theories That Make Probabilistic Predictions. IEEE Intell. Syst. 24 (1) (2009)
Mark Crowley, John Nelson, David Poole
Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making. UAI (2009)
David Poole, Clinton Smyth, Rita Sharma
Semantic Science: Ontologies, Data and Probabilistic Theories. URSW (LNCS Vol.) (2008)
David Poole, Clinton Smyth, Rita Sharma
Semantic Science and Machine-Accessible Scientific Theories. AAAI Spring Symposium: Semantic Scientific Knowledge Integration (2008)
Saleema Amershi, Giuseppe Carenini, Cristina Conati, Alan K. Mackworth, David Poole
Pedagogy and usability in interactive algorithm visualizations: Designing and evaluating CIspace. Interact. Comput. 20 (1) (2008)
Rita Sharma, David Poole, Clinton Smyth
A System for Ontologically-Grounded Probabilistic Matching. BMA (2007)
David Poole
Logical Generative Models for Probabilistic Reasoning about Existence, Roles and Identity. AAAI (2007)
Mark Crowley, Brent Boerlage, David Poole
Adding Local Constraints to Bayesian Networks. Canadian Conference on AI (2007)
Rita Sharma, David Poole
Probability and Equality: A Probabilistic Model of Identity Uncertainty. Canadian Conference on AI (2005)
Saleema Amershi, N. Arksey, Giuseppe Carenini, Cristina Conati, Alan K. Mackworth, Heather Maclaren, David Poole
Designing CIspace: pedagogy and usability in a learning environment for AI. ITiCSE (2005)
Rita Sharma, David Poole
Probabilistic Reasoning with Hierarchically Structured Variables. IJCAI (2005)
Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole
Nonparametric Bayesian Logic. UAI (2005)
David Poole, Clinton Smyth
Type Uncertainty in Ontologically-Grounded Qualitative Probabilistic Matching. ECSQARU (2005)
Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, David Poole
Preference-Based Constrained Optimization with CP-Nets. Comput. Intell. 20 (2) (2004)
Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, David Poole
CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements. J. Artif. Intell. Res. 21 (2004)
David Poole
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach. KDD (2004)
Nando de Freitas, Richard Dearden, Frank Hutter, Rubén Morales-Menéndez, Jim Mutch, David Poole
Diagnosis by a waiter and a Mars explorer. Proc. IEEE 92 (3) (2004)
Clinton Smyth, David Poole
Qualitative Probabilistic Matching with Hierarchical Descriptions. KR (2004)
David Poole
First-order probabilistic inference. IJCAI (2003)
Rita Sharma, David Poole
Efficient Inference in Large Discrete Domains. UAI (2003)
Rubén Morales-Menéndez, Nando de Freitas, David Poole
Estimation and control of industrial processes with particle filters. ACC (2003)
Giuseppe Carenini, Jocelyin Smith, David Poole
Towards more conversational and collaborative recommender systems. IUI (2003)
Rubén Morales-Menéndez, Nando de Freitas, David Poole
Real-Time Monitoring of Complex Industrial Processes with Particle Filters. NIPS (2002)
Rita Sharma, David Poole
Symmetric Collaborative Filtering Using the Noisy Sensor Model. UAI (2001)
David Poole
Logic, Knowledge Representation, and Bayesian Decision Theory. Computational Logic (2000)
David Poole
Abducing through negation as failure: stable models within the independent choice logic. J. Log. Program. 44 (1-3) (2000)
Peter Gorniak, David Poole
Building a Stochastic Dynamic Model of Application Use. UAI (2000)
Peter Gorniak, David Poole
Predicting Future User Actions by Observing Unmodified Applications. AAAI/IAAI (2000)

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Publication Activity (10 Years)

Top Topics

Top Venues

David Poole