David Poole

Vaidyanathan Ramaswami, David Poole, S. Ahm, 2003, 2003 IEEE Pacific Rim Conference on Communications Computers and Signal Processing (PACRIM 2003) (Cat. No.03CH37490).

The Independent Choice Logic for Modelling Multiple Agents Under Uncertainty

David Poole, D. Poole, 1997, Artif. Intell..

Predicting Future User Actions by Observing Unmodified Applications

David Poole, Peter Gorniak, 2000, AAAI/IAAI.

Foundations of model construction in feature-based semantic science

David Poole, D. Poole, 2013, J. Log. Comput..

Decision Theory, the Situation Calculus and Conditional Plans

David Poole, D. Poole, 1998, Electron. Trans. Artif. Intell..

Adapting Decision Theory for Multimedia Presentation Design: User Modelling for Intent-based Authoring

David Poole, Andrew Csinger, 1996, ECAI.

Representing Diagnostic Knowledge for Probabilistic Horn Abduction

David Poole, D. Poole, 1991, IJCAI.

Preference‐Based Constrained Optimization with CP‐Nets

Ronen I. Brafman, Craig Boutilier, Carmel Domshlak, 2004, Comput. Intell..

Comparing Aggregators for Relational Probabilistic Models pdf

Seyed Mehran Kazemi, Xing Zeng, David Poole, 2017, ArXiv.

Learning, Bayesian Probability, Graphical Models, and Abduction

David Poole, D. Poole, 2000 .

Normality and Faults in Logic-Based Diagnosis

David Poole, D. Poole, 1989, IJCAI.

Dialectics and specificity: conditioning in logic-based hypothetical reasoning (preliminary report)

David Poole, D. Poole, 1990 .

An expert system for educational diagnosis based on default logic

David Poole, M Jones, D. Poole, 1987 .

Interactive Visualization for Group Decision Analysis

Giuseppe Carenini, Gunilla Öberg, Hamed Taheri, 2018, Int. J. Inf. Technol. Decis. Mak..

A New Kid on the Block: Application of Julia to Hartree-Fock Calculations.

David Poole, Mark S Gordon, Jorge L Galvez Vallejo, 2020, Journal of chemical theory and computation.

AI meets authoring : user models for intelligent multimedia

Kellogg S. Booth, David Poole, Andrew Csinger, 1995 .

AISpace2: An Interactive Visualization Tool for Learning and Teaching Artificial Intelligence

David Poole, Hanbo Yang, Alan Mackworth, 2020, AAAI.

Explanation and prediction: an architecture for default and abductive reasoning

David Poole, D. Poole, 1989, Comput. Intell..

Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations

Craig Boutilier, David Poole, Craig Boutilier, 1996, AAAI/IAAI, Vol. 2.

Type Uncertainty in Ontologically-Grounded Qualitative Probabilistic Matching

David Poole, Clinton Smyth, D. Poole, 2005, ECSQARU.

Gracefully adding negation and disjunction to Prolog

Randy Goebel, David Poole, 1986, ICLP.

Context-specific approximation in probabilistic inference

David Poole, D. Poole, 1998, UAI.

Domain Recursion for Lifted Inference with Existential Quantifiers pdf

Guy Van den Broeck, Seyed Mehran Kazemi, David Poole, 2017, ArXiv.

The use of conflicts in searching Bayesian networks

David Poole, D. Poole, 1993, UAI.

Building a Stochastic Dynamic Model of Application Use

David Poole, Peter Gorniak, 2000, UAI.

Symmetric Collaborative Filtering Using the Noisy Sensor Model

David Poole, Rita Sharma, D. Poole, 2001, UAI.

Probabilistic Conflicts in a Search Algorithm for Estimating Posterior Probabilities in Bayesian Networks

David Poole, D. Poole, 1996, Artif. Intell..

Lazy Arithmetic Circuits

Seyed Mehran Kazemi, David Poole, D. Poole, 2016, AAAI Workshop: Beyond NP.

On the Comparison of Theories: Preferring the Most Specific Explanation

David Poole, D. Poole, 1985, IJCAI.

Nonparametric Bayesian Logic

Nando de Freitas, David Poole, Peter Carbonetto, 2005, UAI.

Statistical Relational Artificial Intelligence: Logic, Probability, and Computation

Luc De Raedt, Kristian Kersting, Sriraam Natarajan, 2016, Statistical Relational Artificial Intelligence.

Constraint Processing in Lifted Probabilistic Inference pdf

David Poole, Jacek Kisynski, D. Poole, 2009, UAI.

Using Definite Clauses and Integrity Constraints as the Basis for a Theory Formation Approach to Diagnostic Reasoning

Koichi Furukawa, Randy Goebel, David Poole, 1986, ICLP.

CILOG User Manual Version 0.14

David Poole, 2004 .

Exploring Localization in Bayesian Networks for Large Expert Systems pdf

Yang Xiang, David Poole, Michael P. Beddoes, 1992, UAI.

RelNN: A Deep Neural Model for Relational Learning

Seyed Mehran Kazemi, David Poole, D. Poole, 2017, AAAI.

A methodology for using a default and abductive reasoning system

David Poole, D. Poole, 1989, Int. J. Intell. Syst..

Average-Case Analysis of a Search Algorithm for Estimating Prior and Posterior Probabilities in Bayesian Networks with Extreme Probabilities

David Poole, D. Poole, 1993, IJCAI.

Probabilistic Reasoning with Hierarchically Structured Variables

David Poole, Rita Sharma, 2005, IJCAI.

Multiply sectioned Bayesian networks for neuromuscular diagnosis

Yang Xiang, David Poole, Michael P. Beddoes, 1993, Artif. Intell. Medicine.

From Utterance to Belief via Presupposition: Default Logic in User-Modelling

David Poole, Andrew Csinger, 1989, KBCS.

The AAAI-13 Conference Workshops

Diane J. Cook, Christopher W. Geib, Gita Reese Sukthankar, 2013, AI Mag..

Representation, Reasoning, and Learning for a Relational Influence Diagram Applied to a Real-Time Geological Domain

David Poole, Andrew Bamber, Andrew Csinger, 2016, Canadian Conference on AI.

On eliminating loops in Prolog

Randy Goebel, David Poole, 1985, SIGP.

Reasoning With Conditional Ceteris Paribus Preference Statements

Ronen I. Brafman, Craig Boutilier, Holger H. Hoos, 1999, UAI.

First-order probabilistic inference

David Poole, D. Poole, 2003, IJCAI.

Lifted Aggregation in Directed First-Order Probabilistic Models

David Poole, Jacek Kisynski, 2009, IJCAI.

Semantic Science and Machine-Accessible Scientific Theories

David Poole, Rita Sharma, Clinton Smyth, 2008, AAAI Spring Symposium: Semantic Scientific Knowledge Integration.

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2010, Atlanta, Georgia, USA, July 11-15, 2010

Maria Fox, David Poole, D. Poole, 2010, AAAI.

Artificial Intelligence: Agent Architectures and Hierarchical Control

Alan K. Mackworth, David Poole, D. Poole, 2010 .

Real-Time Monitoring of Complex Industrial Processes with Particle Filters

Nando de Freitas, Rubén Morales-Menéndez, David Poole, 2002, NIPS.

Local Users Guide to Theorist

David Poole, 2009 .

Logic, Probability and Computation: Foundations and Issues of Statistical Relational AI

David Poole, D. Poole, 2011, LPNMR.

Management: Foundations and Applications, 2nd Asia Pacific Edition

Alan Simon, David Poole, Paul Davidson, 2013 .

Identity and verification in the digital age: Where we are today and what the future could hold

David Poole, D. Poole, 2017 .

Representing diagnosis knowledge

David Poole, D. Poole, 1994, Annals of Mathematics and Artificial Intelligence.

Dynamic modelling and control of industrial processes with particle filtering algorithms

Ruben Morales-Menendez, Nando de Freitas, David Poole, 2004 .

The Independent Choice Logic and Beyond

David Poole, D. Poole, 2008, Probabilistic Inductive Logic Programming.

A Learning Algorithm for Relational Logistic Regression: Preliminary Results pdf

Seyed Mehran Kazemi, David Poole, Bahare Fatemi, 2016, ArXiv.

Population Size Extrapolation in Relational Probabilistic Modelling

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2014, SUM.

Hypothetically Speaking Default Reasoning and Discourse-Structure

David Poole, Andrew Csinger, 1993, IJCAI.

Pedagogy and usability in interactive algorithm visualizations: Designing and evaluating CIspace

Cristina Conati, Giuseppe Carenini, Alan K. Mackworth, 2016, Interact. Comput..

What the Lottery Paradox Tells Us About Default Reasoning

David Poole, D. Poole, 1989, KR.

A Logical Framework for Default Reasoning

David Poole, D. Poole, 1988, Artif. Intell..

A Search Algorithm for Latent Variable Models with Unbounded Domains

David Poole, Michael Chiang, D. Poole, 2012, AAAI.

Designing and deploying usetube, google's global user experience observation and recording system.

David Poole, Rudy Schusteritsch, Mark LaRosa, 2009, CHI Extended Abstracts.

Mathematical Preliminaries and Notation

Alan K. Mackworth, David Poole, D. Poole, 2010 .

New Liftable Classes for First-Order Probabilistic Inference

Guy Van den Broeck, Seyed Mehran Kazemi, David Poole, 2016, NIPS.

Diagnosis by a waiter and a Mars explorer

Nando de Freitas, Rubén Morales-Menéndez, Frank Hutter, 2004, Proceedings of the IEEE.

Elimination Ordering in Lifted First-Order Probabilistic Inference

Seyed Mehran Kazemi, David Poole, D. Poole, 2014, AAAI.

Probabilistic Reasoning with Undefined Properties in Ontologically-Based Belief Networks

David Poole, David Buchman, Arzoo Katiyar, 2013, IJCAI.

Probability and Equality: A Probabilistic Model of Identity Uncertainty

David Poole, Rita Sharma, 2005, Canadian Conference on AI.

Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (1994) pdf

Ramón López de Mántaras, David Poole, 2013, ArXiv.

Dimensions of complexity of intelligent agents

Alan K. Mackworth, David Poole, Alan Mackworth, 2006, PCAR '06.

AI meets authoring: User models for untelligent multimedia

Kellogg S. Booth, David Poole, Andrew Csinger, 2004, Artificial Intelligence Review.

Ontology Design for Scientific Theories That Make Probabilistic Predictions

David Poole, Rita Sharma, Clinton Smyth, 2009, IEEE Intelligent Systems.

Probabilsitic semantics and defaults pdf

Eric Neufeld, David Poole, Romas Aleliunas, 2013, UAI.

Abducing through negation as failure: stable models within the independent choice logic

David Poole, D. Poole, 2000, J. Log. Program..

Beautiful Data: The Stories Behind Elegant Data Solutions

Antony J. Williams, Peter Norvig, Jeffrey Heer, 2009 .

Structure learning for relational logistic regression: an ensemble approach

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2018, Data Mining and Knowledge Discovery.

Efficient Inference in Large Discrete Domains

David Poole, Rita Sharma, D. Poole, 2002, UAI.

Probabilistic Partial Evaluation: Exploiting Rule Structure in Probabilistic Inference

David Poole, D. Poole, 1997, IJCAI.

Representing Knowledge for Logic-Based Diagnosis

David Poole, D. Poole, 1988, FGCS.

Towards Completely Lifted Search-based Probabilistic Inference pdf

Fahiem Bacchus, David Poole, Jacek Kisynski, 2011, ArXiv.

Planning Under Uncertainty

Alan K. Mackworth, David Poole, 2010 .

Artificial Intelligence: Bibliography

Alan K. Mackworth, David Poole, 2010 .

Plug and Play Integration through Space Object Standardization

David Poole, Jeffrey Shaw, William Branch, 1999 .

Fast Fashion 2D mix Fix - a Slashstroke project

David Poole, Lucy Fine, 2014 .

ILP turns 20

Luc De Raedt, Katsumi Inoue, Ashwin Srinivasan, 2011, Machine Learning.

Artificial Intelligence: Beyond Supervised Learning

Alan K. Mackworth, David Poole, 2010 .

Query Answering in Circumscription

Katsumi Inoue, David Poole, Nicolas Helft, 1991, IJCAI.

On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models

Mark W. Schmidt, Nando de Freitas, David Poole, 2012, AISTATS.

Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models

Seyed Mehran Kazemi, David Poole, D. Poole, 2018, Front. Robot. AI.

Reference classes and relational learning

David Poole, Michael Chiang, D. Poole, 2012, Int. J. Approx. Reason..

Cyclic Causal Models with Discrete Variables: Markov Chain Equilibrium Semantics and Sample Ordering

David Poole, Mark Crowley, 2013, IJCAI.

On Integrating Ontologies with Relational Probabilistic Models

David Poole, Chia-Li Kuo, D. Poole, 2013, StarAI@AAAI.

Relational Logistic Regression

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2014, KR.

Reasoning with conditional ceteris paribus statements

Ronen I. Brafman, Craig Boutilier, Holger H. Hoos, 1999, UAI 1999.

Knowledge Hypergraphs: Prediction Beyond Binary Relations

David Poole, Perouz Taslakian, Bahare Fatemi, 2019, IJCAI.

A framework for ontologically-grounded probabilistic matching

David Poole, Rita Sharma, Clinton Smyth, 2010, Int. J. Approx. Reason..

Semantic e-Science and Geology

David Poole, Rita Sharma, Clinton Smyth, 2007 .

Artificial Intelligence

Alan K. Mackworth, David Poole, D. Poole, 2010 .

Improved Knowledge Graph Embedding using Background Taxonomic Information pdf

Siamak Ravanbakhsh, David Poole, Bahare Fatemi, 2018, AAAI.

The Effect of Knowledge on Belief: Conditioning, Specificity and the Lottery Paradox in Default Reasoning

David Poole, D. Poole, 1991, Artif. Intell..

CISpace: tools for learning computational intelligence

Alan K. Mackworth, David Poole, 2001 .

Adding Local Constraints to Bayesian Networks

David Poole, Mark Crowley, Brent Boerlage, 2007, Canadian Conference on AI.

Relational Logistic Regression: The Directed Analog of Markov Logic Networks

Kristian Kersting, Sriraam Natarajan, Seyed Mehran Kazemi, 2014, StarAI@AAAI.

Computational intelligence - a logical approach

Randy Goebel, Alan K. Mackworth, David Poole, 1998 .

Predicting Landslides Using Locally Aligned Convolutional Neural Networks

David Poole, Ainaz Hajimoradlou, Gioachino Roberti, 2020, IJCAI.

Logic, Knowledge Representation, and Bayesian Decision Theory

David Poole, D. Poole, 2000, Computational Logic.

Negative probabilities in probabilistic logic programs

David Poole, David Buchman, 2017, Int. J. Approx. Reason..

Features and Constraints

Alan K. Mackworth, David Poole, 2010 .

Exploiting the Rule Structure for Decision Making within the Independent Choice Logic

David Poole, D. Poole, 1995, UAI.

Semantic Science: Ontologies, Data and Probabilistic Theories

David Poole, Rita Sharma, Clinton Smyth, 2008, URSW.

Variables in Hypotheses

David Poole, 1987, IJCAI.

Knowledge Hypergraph Embedding Meets Relational Algebra pdf

David Poole, Perouz Taslakian, Bahare Fatemi, 2021, J. Mach. Learn. Res..

The use of logic

David Poole, 1987 .

Artificial Intelligence: Learning: Overview and Supervised Learning

Alan K. Mackworth, David Poole, 2010 .

Fostering Student Learning and Motivation : an Interactive Educational Tool for AI

Cristina Conati, Giuseppe Carenini, Heather Maclaren, 2005 .

Artificial Intelligence: Artificial Intelligence and Agents

Alan K. Mackworth, David Poole, D. Poole, 2010 .

Logical Argumentation, Abduction and Bayesian Decision Theory: A Bayesian Approach to Logical Arguments and Its Application to Legal Evidential Reasoning

David Poole, D. Poole, 2002 .

Decision Graph Search

David Poole, Runping Qi, 1993 .

Two Algorithms for Decision Tree Search

David Poole, Runping Qi, 1992 .

Uncertainty in artificial intelligence : proceedings of the Eleventh Conference (1995) : August 18-20, 1995, Eleventh Conference on Uncertainty in Artificial Intelligence, McGill University, Montréal, Canada

Philippe Besnard, Steve Hanks, David Poole, 1995 .