Neider, Daniel

12 publications

ECML-PKDD 2025 Decentralizing Multi-Agent Reinforcement Learning with Temporal Causal Information Jan Corazza, Hadi Partovi Aria, Hyohun Kim, Daniel Neider, Zhe Xu

NeurIPS 2025 NoBOOM: Chemical Process Datasets for Industrial Anomaly Detection Dennis Wagner, Fabian Hartung, Justus Arweiler, Aparna Muraleedharan, Indra Jungjohann, Arjun Nair, Steffen Reithermann, Ralf Schulz, Michael Bortz, Daniel Neider, Heike Leitte, Joachim Pfeffinger, Stephan Mandt, Sophie Fellenz, Torsten Katz, Fabian Jirasek, Jakob Burger, Hans Hasse, Marius Kloft

AAAI 2025 Temporal Conjunctive Query Answering via Rewriting Lukas Westhofen, Jean Christoph Jung, Daniel Neider

CLeaR 2024 Expediting Reinforcement Learning by Incorporating Knowledge About Temporal Causality in the Environment Jan Corazza, Hadi Partovi Aria, Daniel Neider, Zhe Xu

NeurIPSW 2023 Defending Our Privacy with Backdoors Dominik Hintersdorf, Lukas Struppek, Daniel Neider, Kristian Kersting

NeurIPSW 2023 Expediting Reinforcement Learning by Incorporating Temporal Causal Information Jan Corazza, Hadi Partovi Aria, Daniel Neider, Zhe Xu

AAAI 2023 Learning Interpretable Temporal Properties from Positive Examples Only Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari, Daniel Neider, Zhe Xu, Ufuk Topcu

IJCAI 2022 Neuro-Symbolic Verification of Deep Neural Networks Xuan Xie, Kristian Kersting, Daniel Neider

AAAI 2022 Reinforcement Learning with Stochastic Reward Machines Jan Corazza, Ivan Gavran, Daniel Neider

AAAI 2021 Advice-Guided Reinforcement Learning in a Non-Markovian Environment Daniel Neider, Jean-Raphaël Gaglione, Ivan Gavran, Ufuk Topcu, Bo Wu, Zhe Xu

IJCAI 2020 Learning Interpretable Models in the Property Specification Language Rajarshi Roy, Dana Fisman, Daniel Neider

ECML-PKDD 2020 Quality Guarantees for Autoencoders via Unsupervised Adversarial Attacks Benedikt Böing, Rajarshi Roy, Emmanuel Müller, Daniel Neider