Oliver Schulte

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 59

Top Venues

CoRR

NeurIPS

IJCAI

Data Min. Knowl. Discov.

Publications

Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley
Disentanglement in Implicit Causal Models via Switch Variable. CoRR (2024)
Oliver Schulte, Pascal Poupart
Why Online Reinforcement Learning is Causal. CoRR (2024)
Oliver Schulte
From Graph Generation to Graph Classification. CoRR (2023)
Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. AISTATS (2023)
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting. CoRR (2023)
Manfred Jaeger, Antonio Longa, Steve Azzolin, Oliver Schulte, Andrea Passerini
A Simple Latent Variable Model for Graph Learning and Inference. LoG (2023)
Parmis Naddaf, Erfaneh Mahmoudzaheh Ahmadi Nejad, Kiarash Zahirnia, Manfred Jaeger, Oliver Schulte
Joint Link Prediction Via Inference from a Model. CIKM (2023)
Xiangyu Sun, Oliver Schulte
Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing. CoRR (2023)
Xiangyu Sun, Oliver Schulte
Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing. NeurIPS (2023)
Kiarash Zahirnia, Yaochen Hu, Mark Coates, Oliver Schulte
Neural Graph Generation from Graph Statistics. NeurIPS (2023)
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting. ICML (2023)
Oliver Schulte
Computing Expected Motif Counts for Exchangeable Graph Generative Models. CoRR (2023)
Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart
Distributional Reinforcement Learning with Monotonic Splines. ICLR (2022)
Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. NeurIPS (2022)
Oliver Schulte
Valuing Actions and Ranking Hockey Players With Machine Learning. LINHAC (2022)
Kiarash Zahirnia, Oliver Schulte, Parmis Nadaf, Ke Li
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders. CoRR (2022)
Kiarash Zahirnia, Oliver Schulte, Ke Li, Ankita Sakhuja, Parmis Nadaf
Deep Learning of Latent Edge Types from Relational Data. AI (2022)
Kiarash Zahirnia, Oliver Schulte, Parmis Nadaf, Ke Li
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders. NeurIPS (2022)
Richard Mar, Oliver Schulte
Pre and Post Counting for Scalable Statistical-Relational Model Discovery. CoRR (2021)
Kiarash Zahirnia, Ankita Sakhuja, Oliver Schulte, Parmis Nadaf, Ke Li, Xia Hu
Generating the Graph Gestalt: Kernel-Regularized Graph Representation Learning. CoRR (2021)
Mohan Zhang, Oliver Schulte, Yudong Luo
Leveraging Approximate Constraints for Localized Data Error Detection. aiDM@SIGMOD (2021)
Xiangyu Sun, Guiliang Liu, Pascal Poupart, Oliver Schulte
NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge. CoRR (2021)
Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning. NeurIPS (2021)
Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu
Cracking the Black Box: Distilling Deep Sports Analytics. CoRR (2020)
Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu
Cracking the Black Box: Distilling Deep Sports Analytics. KDD (2020)
Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan
Learning Agent Representations for Ice Hockey. NeurIPS (2020)
Fatemeh Riahi, Oliver Schulte
Model-based exception mining for object-relational data. Data Min. Knowl. Discov. 34 (3) (2020)
Manfred Jaeger, Oliver Schulte
A Complete Characterization of Projectivity for Statistical Relational Models. CoRR (2020)
Manfred Jaeger, Oliver Schulte
A Complete Characterization of Projectivity for Statistical Relational Models. IJCAI (2020)
Guiliang Liu, Yudong Luo, Oliver Schulte, Tarak Kharrat
Deep soccer analytics: learning an action-value function for evaluating soccer players. Data Min. Knowl. Discov. 34 (5) (2020)
Yudong Luo, Oliver Schulte, Pascal Poupart
Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players. IJCAI (2020)
Jing Nathan Yan, Oliver Schulte, Mohan Zhang, Jiannan Wang, Reynold Cheng
SCODED: Statistical Constraint Oriented Data Error Detection. SIGMOD Conference (2020)
Mahmoud Khademi, Oliver Schulte
Deep Generative Probabilistic Graph Neural Networks for Scene Graph Generation. AAAI (2020)
Oliver Schulte, Zhensong Qian
FACTORBASE: multi-relational structure learning with SQL all the way. Int. J. Data Sci. Anal. 7 (4) (2019)
Jing Nathan Yan, Oliver Schulte, Jiannan Wang, Reynold Cheng
Detecting Data Errors with Statistical Constraints. CoRR (2019)
Oliver Schulte
Causal Learning with Occam's Razor. Stud Logica 107 (5) (2019)
Guiliang Liu, Oliver Schulte
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. IJCAI (2018)
Mahmoud Khademi, Oliver Schulte
Image Caption Generation With Hierarchical Contextual Visual Spatial Attention. CVPR Workshops (2018)
Yejia Liu, Oliver Schulte, Chao Li
Model Trees for Identifying Exceptional Players in the NHL and NBA Drafts. MLSA@PKDD/ECML (2018)
Manfred Jaeger, Oliver Schulte
Inference, Learning, and Population Size: Projectivity for SRL Models. CoRR (2018)
Fatemeh Riahi, Oliver Schulte
Model-based Exception Mining for Object-Relational Data. CoRR (2018)
Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. ECML/PKDD (2) (2018)
Guiliang Liu, Oliver Schulte
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. CoRR (2018)
Oliver Schulte, Yejia Liu, Chao Li
Model Trees for Identifying Exceptional Players in the NHL Draft. CoRR (2018)
Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. CoRR (2018)
Guiliang Liu, Wang Zhu, Oliver Schulte
Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL. MLSA@PKDD/ECML (2018)
Mahmoud Khademi, Oliver Schulte
Dynamic Gated Graph Neural Networks for Scene Graph Generation. ACCV (6) (2018)
Oliver Schulte, Mahmoud Khademi, Sajjad Gholami, Zeyu Zhao, Mehrsan Javan Roshtkhari, Philippe Desaulniers
A Markov Game model for valuing actions, locations, and team performance in ice hockey. Data Min. Knowl. Discov. 31 (6) (2017)
Oliver Schulte, Sajjad Gholami
Locally Consistent Bayesian Network Scores for Multi-Relational Data. IJCAI (2017)
Oliver Schulte, Zhensong Qian, Arthur E. Kirkpatrick, Xiaoqian Yin, Yan Sun
Fast learning of relational dependency networks. Mach. Learn. 103 (3) (2016)
Fatemeh Riahi, Oliver Schulte
Propositionalization for Unsupervised Outlier Detection in Multi-Relational Data. FLAIRS Conference (2016)
David Beaudoin, Oliver Schulte, Tim B. Swartz
Biased penalty calls in the National Hockey League. Stat. Anal. Data Min. 9 (5) (2016)
Fatemeh Riahi, Oliver Schulte
Model-Based Outlier Detection for Object-Relational Data. SSCI (2015)
Oliver Schulte, Zeyu Zhao, Kurt Routley
What is the Value of an Action in Ice Hockey? Q-Learning for the NHL. MLSA@PKDD/ECML (2015)
Kurt Routley, Oliver Schulte
A Markov Game Model for Valuing Player Actions in Ice Hockey. UAI (2015)
Oliver Schulte, Zhensong Qian
SQL for SRL: Structure Learning Inside a Database System. CoRR (2015)
Jan Motl, Oliver Schulte
The CTU Prague Relational Learning Repository. CoRR (2015)
Oliver Schulte, Zhensong Qian
FactorBase: SQL for Learning A Multi-Relational Graphical Model. CoRR (2015)
Zhensong Qian, Oliver Schulte
FactorBase : Multi-relational model learning with SQL all the way. DSAA (2015)
Zhensong Qian, Oliver Schulte, Yan Sun
Computing Multi-Relational Sufficient Statistics for Large Databases. CIKM (2014)
Oliver Schulte, Kurt Routley
Aggregating predictions vs. aggregating features for relational classification. CIDM (2014)
Oliver Schulte, Hassan Khosravi, Arthur E. Kirkpatrick, Tianxiang Gao, Yuke Zhu
Modelling relational statistics with Bayes Nets. Mach. Learn. 94 (1) (2014)
Fatemeh Riahi, Oliver Schulte, Qing Li
A Proposal for Statistical Outlier Detection in Relational Structures. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Zhensong Qian, Oliver Schulte, Yan Sun
Computing Multi-Relational Sufficient Statistics for Large Databases. CoRR (2014)
Oliver Schulte, Zhensong Qian, Arthur E. Kirkpatrick, Xiaoqian Yin, Yan Sun
Fast Learning of Relational Dependency Networks. CoRR (2014)
Zhensong Qian, Oliver Schulte
Learning Bayes Nets for Relational Data with Link Uncertainty. GKR (2013)
Oliver Schulte, Bahareh Bina, Branden Crawford, D. Bingham, Yi Xiong
A hierarchy of independence assumptions for multi-relational Bayes net classifiers. CIDM (2013)
Bahareh Bina, Oliver Schulte, Branden Crawford, Zhensong Qian, Yi Xiong
Simple decision forests for multi-relational classification. Decis. Support Syst. 54 (3) (2013)
Oliver Schulte, Fatemeh Riahi, Qing Li
Identifying Important Nodes in Heterogenous Networks. AAAI (Late-Breaking Developments) (2013)
Byron J. Gao, Martin Ester, Hui Xiong, Jin-Yi Cai, Oliver Schulte
The Minimum Consistent Subset Cover Problem: A Minimization View of Data Mining. IEEE Trans. Knowl. Data Eng. 25 (3) (2013)
Hassan Khosravi, Ali Bozorgkhan, Oliver Schulte
Transaction-based link strength prediction in a social network. CIDM (2013)
Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao
Learning compact Markov logic networks with decision trees. Mach. Learn. 89 (3) (2012)
Oliver Schulte, Hassan Khosravi, Tong Man
Learning directed relational models with recursive dependencies. Mach. Learn. 89 (3) (2012)
Oliver Schulte, Hassan Khosravi
Learning graphical models for relational data via lattice search. Mach. Learn. 88 (3) (2012)
Oliver Schulte, Hassan Khosravi, Tianxiang Gao, Yuke Zhu
Random Regression for Bayes Nets Applied to Relational Data. StarAI@UAI (2012)
Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao
Learning Compact Markov Logic Networks with Decision Trees. ILP (2011)
Oliver Schulte, Hassan Khosravi, Tong Man
Learning Directed Relational Models with Recursive Dependencies. ILP (2011)
Oliver Schulte
A Tractable Pseudo-Likelihood Function for Bayes Nets Applied to Relational Data. SDM (2011)
Petra Berenbrink, Oliver Schulte
Evolutionary equilibrium in Bayesian routing games: Specialization and niche formation. Theor. Comput. Sci. 411 (7-9) (2010)
Oliver Schulte, Wei Luo, Russell Greiner
Mind change optimal learning of Bayes net structure from dependency and independency data. Inf. Comput. 208 (1) (2010)
Oliver Schulte, Mark S. Drew
Discovery of Conservation Laws via Matrix Search. Discovery Science (2010)
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyuan Xu, Bahareh Bina
Structure Learning for Markov Logic Networks with Many Descriptive Attributes. AAAI (2010)
Oliver Schulte, Gustavo Frigo, Russell Greiner, Hassan Khosravi
The IMAP Hybrid Method for Learning Gaussian Bayes Nets. Canadian Conference on AI (2010)
Oliver Schulte, Gustavo Frigo, Russell Greiner, Wei Luo, Hassan Khosravi
A new hybrid method for Bayesian network learning With dependency constraints. CIDM (2009)
Bahareh Bina, Oliver Schulte, Hassan Khosravi
LNBC: A Link-Based Naive Bayes Classifier. ICDM Workshops (2009)
Oliver Schulte
Simultaneous Discovery of Conservation Laws and Hidden Particles with Smith Matrix Decomposition. IJCAI (2009)
Oliver Schulte, Hassan Khosravi, Flavia Moser, Martin Ester
Join Bayes Nets: A new type of Bayes net for relational data CoRR (2008)
Petra Berenbrink, Oliver Schulte
Evolutionary Equilibrium in Bayesian Routing Games: Specialization and Niche Formation. ESA (2007)
Oliver Schulte, Wei Luo, Russell Greiner
Mind Change Optimal Learning of Bayes Net Structure. COLT (2007)
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Schulte, Hui Xiong
The minimum consistent subset cover problem and its applications in data mining. KDD (2007)
Oliver Schulte, Flavia Moser, Martin Ester, Zhiyong Lu
Association Rules in the Relational Calculus CoRR (2007)
Wei Luo, Oliver Schulte
Mind change efficient learning. Inf. Comput. 204 (6) (2006)
Wei Luo, Oliver Schulte
Mind Change Efficient Learning. COLT (2005)
Oliver Schulte, James P. Delgrande
Representing von Neumann-Morgenstern Games in the Situation Calculus. Ann. Math. Artif. Intell. 42 (1-3) (2004)
Oliver Schulte
Iterated backward inference: an algorithm for proper rationalizability. TARK (2003)
Bradley Bart, James P. Delgrande, Oliver Schulte
Knowledge and Planning in an Action-Based Multi-agent Framework: A Case Study. Canadian Conference on AI (2001)
Oliver Schulte
The Logic Of Reliable And Efficient Inquiry. J. Philos. Log. 28 (4) (1999)
Oliver Schulte
Minimal Belief Change and the Pareto Principle. Synth. 118 (3) (1999)
Oliver Schulte
Minimal Belief Change and Pareto-Optimality. Australian Joint Conference on Artificial Intelligence (1999)
Torsten Rohlfing, Jürgen Beier, Oliver Schulte, Norbert Hosten, Roland Felix
Multimodale Registrierung mit effizienten Lernverfahren für neuronale Netze. Bildverarbeitung für die Medizin (1998)

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Publication Activity (10 Years)

Top Topics

Top Venues

Oliver Schulte