Tschiatschek, Sebastian

44 publications

ICLR 2025 Breaking the Reclustering Barrier in Centroid-Based Deep Clustering Lukas Miklautz, Timo Klein, Kevin Sidak, Collin Leiber, Thomas Lang, Andrii Shkabrii, Sebastian Tschiatschek, Claudia Plant

TMLR 2025 Expressiveness of Parametrized Distributions over DAGs for Causal Discovery Simon Rittel, Sebastian Tschiatschek

UAI 2025 On Constant Regret for Low-Rank MDPs Alexander Sturm, Sebastian Tschiatschek

ICLRW 2025 ReSL: Enhancing Deep Clustering Through Reset-Based Self-Labeling Andrii Shkabrii, Timo Klein, Lukas Miklautz, Sebastian Tschiatschek, Claudia Plant

IJCAI 2025 Rule-Guided Reinforcement Learning Policy Evaluation and Improvement Martin Tappler, Ignacio D. Lopez-Miguel, Sebastian Tschiatschek, Ezio Bartocci

AISTATS 2024 Learning Safety Constraints from Demonstrations with Unknown Rewards David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

ICMLW 2024 Permutation Tree Invariant Neural Architectures Johannes Urban, Sebastian Tschiatschek, Nils Morten Kriege

JMLR 2024 Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani

ECML-PKDD 2023 Posterior Consistency for Missing Data in Variational Autoencoders Timur Sudak, Sebastian Tschiatschek

ICML 2022 Interactively Learning Preference Constraints in Linear Bandits David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

IJCAI 2022 Option Transfer and SMDP Abstraction with Successor Features Dongge Han, Sebastian Tschiatschek

IJCAI 2021 Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces Lukas Miklautz, Lena G. M. Bauer, Dominik Mautz, Sebastian Tschiatschek, Christian Böhm, Claudia Plant

AAAI 2021 Educational Question Mining at Scale: Prediction, Analysis and Personalization Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang

NeurIPS 2021 Information Directed Reward Learning for Reinforcement Learning David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause

AAAI 2021 Sequential Generative Exploration Model for Partially Observable Reinforcement Learning Haiyan Yin, Jianda Chen, Sinno Jialin Pan, Sebastian Tschiatschek

ICLR 2020 AMRL: Aggregated Memory for Reinforcement Learning Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann

NeurIPSW 2020 Reinforcement Learning with Efficient Active Feature Acquisition Haiyan Yin, Yingzhen Li, Sinno Pan, Cheng Zhang, Sebastian Tschiatschek

NeurIPS 2020 VAEM: A Deep Generative Model for Heterogeneous Mixed Type Data Chao Ma, Sebastian Tschiatschek, Richard Turner, José Miguel Hernández-Lobato, Cheng Zhang

ICMLW 2020 VAEM: A Deep Generative Model for Heterogeneous Mixed Type Data Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang

ICML 2019 EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Miguel Hernandez-Lobato, Sebastian Nowozin, Cheng Zhang

NeurIPS 2019 Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann

NeurIPS 2019 Icebreaker: Element-Wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E Turner, José Miguel Hernández-Lobato, Cheng Zhang

NeurIPS 2019 Learner-Aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla

NeurIPS 2019 Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek

IJCAI 2018 Differentiable Submodular Maximization Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause

AAAI 2018 Learning User Preferences to Incentivize Exploration in the Sharing Economy Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause

NeurIPS 2018 Teaching Inverse Reinforcement Learners via Features and Demonstrations Luis Haug, Sebastian Tschiatschek, Adish Singla

ICML 2017 Guarantees for Greedy Maximization of Non-Submodular Functions with Applications Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek

UAI 2017 Improving Optimization-Based Approximate Inference by Clamping Variables Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

AAAI 2017 Selecting Sequences of Items via Submodular Maximization Sebastian Tschiatschek, Adish Singla, Andreas Krause

ICML 2016 Actively Learning Hemimetrics with Applications to Eliciting User Preferences Adish Singla, Sebastian Tschiatschek, Andreas Krause

NeurIPS 2016 Cooperative Graphical Models Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause

AISTATS 2016 Learning Probabilistic Submodular Diversity Models via Noise Contrastive Estimation Sebastian Tschiatschek, Josip Djolonga, Andreas Krause

AAAI 2016 Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization Adish Singla, Sebastian Tschiatschek, Andreas Krause

NeurIPS 2016 Variational Inference in Mixed Probabilistic Submodular Models Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

ECML-PKDD 2015 Message Scheduling Methods for Belief Propagation Christian Knoll, Michael Rath, Sebastian Tschiatschek, Franz Pernkopf

AISTATS 2015 On Theoretical Properties of Sum-Product Networks Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos

ECML-PKDD 2015 Parameter Learning of Bayesian Network Classifiers Under Computational Constraints Sebastian Tschiatschek, Franz Pernkopf

ECML-PKDD 2015 Structured Regularizer for Neural Higher-Order Sequence Models Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

ECML-PKDD 2014 Integer Bayesian Network Classifiers Sebastian Tschiatschek, Karin Paul, Franz Pernkopf

NeurIPS 2014 Learning Mixtures of Submodular Functions for Image Collection Summarization Sebastian Tschiatschek, Rishabh K Iyer, Haochen Wei, Jeff A. Bilmes

AISTATS 2013 On the Asymptotic Optimality of Maximum Margin Bayesian Networks Sebastian Tschiatschek, Franz Pernkopf

ICML 2013 The Most Generative Maximum Margin Bayesian Networks Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf

ECML-PKDD 2012 Bayesian Network Classifiers with Reduced Precision Parameters Sebastian Tschiatschek, Peter Reinprecht, Manfred Mücke, Franz Pernkopf