Schulte, Oliver

30 publications

TMLR 2025 When Should Reinforcement Learning Use Causal Reasoning? Oliver Schulte, Pascal Poupart

ICMLW 2024 From Graph Diffusion to Graph Classification Jia Jun Cheng Xian, Sadegh Mahdavi, Renjie Liao, Oliver Schulte

ICMLW 2024 Rule-Enhanced Graph Learning Ali Khazraee, Abdolreza Mirzaei, Majjid Farhadi, Parmis Nadaff, Kiarash Zahirnia, Mohammad Salameh, Kevin Cannons, Richard Mar, Mingyi Wu, Oliver Schulte

LoG 2023 A Simple Latent Variable Model for Graph Learning and Inference Manfred Jaeger, Antonio Longa, Steve Azzolin, Oliver Schulte, Andrea Passerini

NeurIPS 2023 Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing Xiangyu Sun, Oliver Schulte

ICML 2023 Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley

AISTATS 2023 NTS-NOTEARS: Learning Nonparametric DBNs with Prior Knowledge Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart

NeurIPS 2023 Neural Graph Generation from Graph Statistics Kiarash Zahirnia, Yaochen Hu, Mark Coates, Oliver Schulte

ICLR 2022 Distributional Reinforcement Learning with Monotonic Splines Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart

NeurIPS 2022 Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li

NeurIPS 2022 Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart

NeurIPS 2021 Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart

IJCAI 2020 A Complete Characterization of Projectivity for Statistical Relational Models Manfred Jaeger, Oliver Schulte

AAAI 2020 Deep Generative Probabilistic Graph Neural Networks for Scene Graph Generation Mahmoud Khademi, Oliver Schulte

IJCAI 2020 Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players Yudong Luo, Oliver Schulte, Pascal Poupart

NeurIPS 2020 Learning Agent Representations for Ice Hockey Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan

IJCAI 2018 Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation Guiliang Liu, Oliver Schulte

CVPRW 2018 Image Caption Generation with Hierarchical Contextual Visual Spatial Attention Mahmoud Khademi, Oliver Schulte

ECML-PKDD 2018 Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li

IJCAI 2017 Locally Consistent Bayesian Network Scores for Multi-Relational Data Oliver Schulte, Sajjad Gholami

MLJ 2016 Fast Learning of Relational Dependency Networks Oliver Schulte, Zhensong Qian, Arthur E. Kirkpatrick, Xiaoqian Yin, Yan Sun

UAI 2015 A Markov Game Model for Valuing Player Actions in Ice Hockey Kurt Routley, Oliver Schulte

MLJ 2014 Modelling Relational Statistics with Bayes Nets Oliver Schulte, Hassan Khosravi, Arthur E. Kirkpatrick, Tianxiang Gao, Yuke Zhu

MLJ 2012 Learning Compact Markov Logic Networks with Decision Trees Hassan Khosravi, Oliver Schulte, Jianfeng Hu, Tianxiang Gao

MLJ 2012 Learning Directed Relational Models with Recursive Dependencies Oliver Schulte, Hassan Khosravi, Tong Man

MLJ 2012 Learning Graphical Models for Relational Data via Lattice Search Oliver Schulte, Hassan Khosravi

AAAI 2010 Structure Learning for Markov Logic Networks with Many Descriptive Attributes Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyuan Xu, Bahareh Bina

IJCAI 2009 Simultaneous Discovery of Conservation Laws and Hidden Particles with Smith Matrix Decomposition Oliver Schulte

COLT 2007 Mind Change Optimal Learning of Bayes Net Structure Oliver Schulte, Wei Luo, Russell Greiner

COLT 2005 Mind Change Efficient Learning Wei Luo, Oliver Schulte