| 2025 | AIED | Synthesizing High-Quality Programming Tasks with LLM-Based Expert and Student Agents. | Manh Hung Nguyen, Victor-Alexandru Padurean, Alkis Gotovos, Sebastian Tschiatschek, Adish Singla |
| 2025 | ICLR | 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 |
| 2025 | IJCAI | Rule-Guided Reinforcement Learning Policy Evaluation and Improvement. | Martin Tappler, Ignacio D. Lopez-Miguel, Sebastian Tschiatschek, Ezio Bartocci |
| 2025 | UAI | On Constant Regret for Low-Rank MDPs. | Alexander Sturm, Sebastian Tschiatschek |
| 2024 | AISTATS | Learning Safety Constraints from Demonstrations with Unknown Rewards. | David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause |
| 2024 | EDM | Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming. | Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla |
| 2023 | ECAI | Specifying Prior Beliefs over DAGs in Deep Bayesian Causal Structure Learning. | Simon Rittel, Sebastian Tschiatschek |
| 2022 | AIED | Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. | Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla |
| 2022 | EDM | Equity and Fairness of Bayesian Knowledge Tracing. | Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla |
| 2022 | ICML | Interactively Learning Preference Constraints in Linear Bandits. | David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause |
| 2022 | IJCAI | Option Transfer and SMDP Abstraction with Successor Features. | Dongge Han, Sebastian Tschiatschek |
| 2021 | AAAI | Educational Question Mining At Scale: Prediction, Analysis and Personalization. | Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, Jos Miguel Hernndez-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang |
| 2021 | AAAI | Sequential Generative Exploration Model for Partially Observable Reinforcement Learning. | Haiyan Yin, Jianda Chen, Sinno Jialin Pan, Sebastian Tschiatschek |
| 2021 | CHI | Social Sensemaking with AI: Designing an Open-ended AI Experience with a Blind Child. | Cecily Morrison, Edward Cutrell, Martin Grayson, Anja Thieme, Alex S. Taylor, Geert Roumen, Camilla Longden, Sebastian Tschiatschek, Rita Faia Marques, Abigail Sellen |
| 2021 | IJCAI | Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces. | Lukas Miklautz, Lena G. M. Bauer, Dominik Mautz, Sebastian Tschiatschek, Christian Bhm, Claudia Plant |
| 2020 | ICLR | AMRL: Aggregated Memory For Reinforcement Learning. | Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann |
| 2019 | ICML | EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. | Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jos Miguel Hernndez-Lobato, Sebastian Nowozin, Cheng Zhang |
| 2019 | IUI | Evaluating Rule-based Programming and ReinforcementLearning for Personalising an Intelligent System. | Ruixue Liu, Advait Sarkar, Erin Solovey, Sebastian Tschiatschek |
| 2018 | AAAI | Learning User Preferences to Incentivize Exploration in the Sharing Economy. | Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause |
| 2018 | IJCAI | Differentiable Submodular Maximization. | Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause |
| 2018 | WWW | Fake News Detection in Social Networks via Crowd Signals. | Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause |
| 2017 | AAAI | Selecting Sequences of Items via Submodular Maximization. | Sebastian Tschiatschek, Adish Singla, Andreas Krause |
| 2017 | ICML | Guarantees for Greedy Maximization of Non-submodular Functions with Applications. | Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek |
| 2017 | Interspeech | Frame and Segment Level Recurrent Neural Networks for Phone Classification. | Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf |
| 2017 | UAI | Improving Optimization-Based Approximate Inference by Clamping Variables. | Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause |
| 2016 | AAAI | Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. | Adish Singla, Sebastian Tschiatschek, Andreas Krause |
| 2016 | AISTATS | Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. | Sebastian Tschiatschek, Josip Djolonga, Andreas Krause |
| 2016 | ICML | Actively Learning Hemimetrics with Applications to Eliciting User Preferences. | Adish Singla, Sebastian Tschiatschek, Andreas Krause |
| 2016 | Interspeech | Virtual Adversarial Training Applied to Neural Higher-Order Factors for Phone Classification. | Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf |
| 2015 | AISTATS | On Theoretical Properties of Sum-Product Networks. | Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos |
| 2015 | Interspeech | Neural higher-order factors in conditional random fields for phoneme classification. | Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf |
| 2013 | AISTATS | On the Asymptotic Optimality of Maximum Margin Bayesian Networks. | Sebastian Tschiatschek, Franz Pernkopf |
| 2013 | ICASSP | Bounds for Bayesian network classifiers with reduced precision parameters. | Sebastian Tschiatschek, Carlos Eduardo Cancino-Chacn, Franz Pernkopf |
| 2013 | ICML | The Most Generative Maximum Margin Bayesian Networks. | Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf |
| 2012 | ICPRAM | Convex Combinations of Maximum Margin Bayesian Network Classifiers. | Sebastian Tschiatschek, Franz Pernkopf |