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ORCIDKristian Kersting
Person information
- affiliation: TU Darmstadt, Computer Science Department, Germany
- affiliation: TU Darmstadt, Centre for Cognitive Science, Germany
- affiliation: TU Dortmund, Department of Computer Science, Germany
- affiliation: University of Bonn, Faculty of Agriculture, Germany
- affiliation: Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin, Germany
- affiliation: Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory (CSAIL), Cambridge, MA, USA
- affiliation (PhD 2005): University of Freiburg, Machine Learning Laborator, Germany
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2020 – today
- 2023
[j66]Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
αILP: thinking visual scenes as differentiable logic programs. Mach. Learn. 112(5): 1465-1497 (2023)- [j65]Felix Friedrich
, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
A typology for exploring the mitigation of shortcut behaviour. Nat. Mac. Intell. 5(3): 319-330 (2023) - [c199]Nandini Ramanan, Phillip Odom, Kristian Kersting, Sriraam Natarajan:
Active Feature Acquisition via Human Interaction in Relational domains. COMAD/CODS 2023: 70-78 - [i116]Mayukh Deb, Björn Deiseroth, Samuel Weinbach, Patrick Schramowski, Kristian Kersting:
AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation. CoRR abs/2301.08110 (2023) - [i115]Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting:
SEGA: Instructing Diffusion using Semantic Dimensions. CoRR abs/2301.12247 (2023) - [i114]Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting:
Probabilistic Circuits That Know What They Don't Know. CoRR abs/2302.06544 (2023) - [i113]Felix Friedrich, Patrick Schramowski, Manuel Brack, Lukas Struppek, Dominik Hintersdorf, Sasha Luccioni, Kristian Kersting:
Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness. CoRR abs/2302.10893 (2023) - [i112]Lukas Struppek, Dominik Hintersdorf, Felix Friedrich, Manuel Brack, Patrick Schramowski, Kristian Kersting:
Image Classifiers Leak Sensitive Attributes About Their Classes. CoRR abs/2303.09289 (2023) - [i111]Felix Friedrich, David Steinmann, Kristian Kersting:
One Explanation Does Not Fit XIL. CoRR abs/2304.07136 (2023) - [i110]Johannes Czech, Jannis Blüml, Kristian Kersting:
Representation Matters: The Game of Chess Poses a Challenge to Vision Transformers. CoRR abs/2304.14918 (2023) - [i109]Jannis Weil, Johannes Czech, Tobias Meuser, Kristian Kersting:
Know your Enemy: Investigating Monte-Carlo Tree Search with Opponent Models in Pommerman. CoRR abs/2305.13206 (2023) - 2022
- [j64]Parisa Kordjamshidi, Dan Roth, Kristian Kersting:
Declarative Learning-Based Programming as an Interface to AI Systems. Frontiers Artif. Intell. 5: 755361 (2022) - [j63]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. 140: 298-313 (2022) - [j62]Matej Petkovic, Michelangelo Ceci, Gianvito Pio, Blaz Skrlj, Kristian Kersting, Saso Dzeroski:
Relational tree ensembles and feature rankings. Knowl. Based Syst. 251: 109254 (2022) - [j61]Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf, Kristian Kersting:
Large pre-trained language models contain human-like biases of what is right and wrong to do. Nat. Mach. Intell. 4(3): 258-268 (2022) - [j60]Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer, Tim Grube, Kristian Kersting, Max Mühlhäuser:
User-Level Label Leakage from Gradients in Federated Learning. Proc. Priv. Enhancing Technol. 2022(2): 227-244 (2022) - [c198]Mei Ling Fang, Devendra Singh Dhami, Kristian Kersting:
DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs. AIME 2022: 178-188 - [c197]Wolfgang Stammer, Marius Memmel, Patrick Schramowski, Kristian Kersting:
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. CVPR 2022: 10307-10318 - [c196]Lukas Struppek, Dominik Hintersdorf, Daniel Neider, Kristian Kersting:
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash. FAccT 2022: 58-69 - [c195]Patrick Schramowski, Christopher Tauchmann, Kristian Kersting:
Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content? FAccT 2022: 1350-1361 - [c194]Felix Friedrich, Patrick Schramowski, Christopher Tauchmann, Kristian Kersting:
Interactively Providing Explanations for Transformer Language Models. HHAI 2022: 285-287 - [c193]Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting:
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability. ICLR 2022 - [c192]Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correia, Antonia Adler, Kristian Kersting:
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. ICML 2022: 20522-20545 - [c191]Mina Ameli, Viktor Pfanschilling, Anar Amirli, Wolfgang Maaß, Kristian Kersting:
Unsupervised Multi-sensor Anomaly Localization with Explainable AI. AIAI (1) 2022: 507-519 - [c190]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
To Trust or Not To Trust Prediction Scores for Membership Inference Attacks. IJCAI 2022: 3043-3049 - [c189]Xuan Xie, Kristian Kersting, Daniel Neider:
Neuro-Symbolic Verification of Deep Neural Networks. IJCAI 2022: 3622-3628 - [c188]Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. KR 2022 - [c187]Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Neural-Probabilistic Answer Set Programming. KR 2022 - [c186]Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting, Iryna Gurevych:
Adaptable Adapters. NAACL-HLT 2022: 3742-3753 - [c185]Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M. Haas, Kristian Kersting, Sriraam Natarajan:
Explaining Deep Tractable Probabilistic Models: The sum-product network case. PGM 2022: 325-336 - [c184]Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting:
Predictive Whittle networks for time series. UAI 2022: 2320-2330 - [i108]Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correia, Antonia Adler, Kristian Kersting:
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. CoRR abs/2201.12179 (2022) - [i107]Xiaoting Shao, Karl Stelzner, Kristian Kersting:
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. CoRR abs/2202.00391 (2022) - [i106]Patrick Schramowski, Christopher Tauchmann, Kristian Kersting:
Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content? CoRR abs/2202.06675 (2022) - [i105]Xuan Xie, Kristian Kersting, Daniel Neider:
Neuro-Symbolic Verification of Deep Neural Networks. CoRR abs/2203.00938 (2022) - [i104]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
A Typology to Explore and Guide Explanatory Interactive Machine Learning. CoRR abs/2203.03668 (2022) - [i103]Katharina Hämmerl, Björn Deiseroth, Patrick Schramowski, Jindrich Libovický, Alexander Fraser, Kristian Kersting:
Do Multilingual Language Models Capture Differing Moral Norms? CoRR abs/2203.09904 (2022) - [i102]Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting:
Finding Structure and Causality in Linear Programs. CoRR abs/2203.15274 (2022) - [i101]Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting, Iryna Gurevych:
Adaptable Adapters. CoRR abs/2205.01549 (2022) - [i100]Xiaoting Shao, Kristian Kersting:
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models. CoRR abs/2205.07774 (2022) - [i99]David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Machines Explaining Linear Programs. CoRR abs/2206.07194 (2022) - [i98]Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation. CoRR abs/2206.07195 (2022) - [i97]Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Towards a Solution to Bongard Problems: A Causal Approach. CoRR abs/2206.07196 (2022) - [i96]Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami:
Attributions Beyond Neural Networks: The Linear Program Case. CoRR abs/2206.07203 (2022) - [i95]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Can Foundation Models Talk Causality? CoRR abs/2206.10591 (2022) - [i94]Jonas Seng, Pooja Prasad, Devendra Singh Dhami, Kristian Kersting:
HANF: Hyperparameter And Neural Architecture Search in Federated Learning. CoRR abs/2206.12342 (2022) - [i93]Manuel Brack, Patrick Schramowski, Björn Deiseroth, Kristian Kersting:
ILLUME: Rationalizing Vision-Language Models by Interacting with their Jabber. CoRR abs/2208.08241 (2022) - [i92]Frieder Uhlig, Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
Transformer-Boosted Anomaly Detection with Fuzzy Hashes. CoRR abs/2208.11367 (2022) - [i91]Björn Deiseroth, Patrick Schramowski, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems. CoRR abs/2208.13518 (2022) - [i90]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models. CoRR abs/2209.07341 (2022) - [i89]Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
The Biased Artist: Exploiting Cultural Biases via Homoglyphs in Text-Guided Image Generation Models. CoRR abs/2209.08891 (2022) - [i88]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Revision Transformers: Getting RiT of No-Nos. CoRR abs/2210.10332 (2022) - [i87]Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models. CoRR abs/2211.02408 (2022) - [i86]Patrick Schramowski, Manuel Brack, Björn Deiseroth, Kristian Kersting:
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models. CoRR abs/2211.05105 (2022) - [i85]Katharina Hämmerl, Björn Deiseroth, Patrick Schramowski, Jindrich Libovický, Constantin A. Rothkopf, Alexander Fraser, Kristian Kersting:
Speaking Multiple Languages Affects the Moral Bias of Language Models. CoRR abs/2211.07733 (2022) - [i84]Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbacher, Dwarak Vittal, Kristian Kersting:
Boosting Object Representation Learning via Motion and Object Continuity. CoRR abs/2211.09771 (2022) - [i83]Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Differentiable Meta logical Programming. CoRR abs/2211.11650 (2022) - [i82]Manuel Brack, Patrick Schramowski, Felix Friedrich, Dominik Hintersdorf, Kristian Kersting:
The Stable Artist: Steering Semantics in Diffusion Latent Space. CoRR abs/2212.06013 (2022) - [i81]Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting:
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges. CoRR abs/2212.12570 (2022) - [i80]Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling:
Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161). Dagstuhl Reports 12(4): 13-25 (2022) - 2021
- [j59]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure learning for relational logistic regression: an ensemble approach. Data Min. Knowl. Discov. 35(5): 2089-2111 (2021) - [j58]Niyati Rawal, Dorothea Koert, Cigdem Turan, Kristian Kersting, Jan Peters, Ruth Stock-Homburg:
ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition. Frontiers Robotics AI 8: 730317 (2021) - [j57]Plinio Moreno, Alexandre Bernardino, José Santos-Victor, Rodrigo M. M. Ventura, Kristian Kersting:
Editorial: Robots that Learn and Reason: Towards Learning Logic Rules from Noisy Data. Frontiers Robotics AI 8: 755933 (2021) - [j56]Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer:
Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation. Frontiers Artif. Intell. 4: 642263 (2021) - [c183]Xiaoting Shao, Arseny Skryagin, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions. AAAI 2021: 9533-9540 - [c182]Johannes Czech, Patrick Korus, Kristian Kersting:
Improving AlphaZero Using Monte-Carlo Graph Search. ICAPS 2021: 103-111 - [c181]Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations. CVPR 2021: 3619-3629 - [c180]Zhongjie Yu, Fabrizio G. Ventola, Kristian Kersting:
Whittle Networks: A Deep Likelihood Model for Time Series. ICML 2021: 12177-12186 - [c179]David Solans, Christopher Tauchmann, Aideen Farrell, Karolin Kappler, Hans-Hendrik Huber, Carlos Castillo, Kristian Kersting:
Learning to Classify Morals and Conventions: Artificial Intelligence in Terms of the Economics of Convention. ICWSM 2021: 691-702 - [c178]Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting:
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP 2021: 251-265 - [c177]Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting:
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. NeurIPS 2021: 15019-15031 - [c176]Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting:
Leveraging probabilistic circuits for nonparametric multi-output regression. UAI 2021: 2008-2018 - [e13]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12457, Springer 2021, ISBN 978-3-030-67657-5 [contents] - [e12]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12458, Springer 2021, ISBN 978-3-030-67660-5 [contents] - [e11]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part III. Lecture Notes in Computer Science 12459, Springer 2021, ISBN 978-3-030-67663-6 [contents] - [i79]Quentin Delfosse, Patrick Schramowski, Alejandro Molina, Kristian Kersting:
Recurrent Rational Networks. CoRR abs/2102.09407 (2021) - [i78]Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting:
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. CoRR abs/2102.10440 (2021) - [i77]Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf, Kristian Kersting:
Language Models have a Moral Dimension. CoRR abs/2103.11790 (2021) - [i76]Karl Stelzner, Kristian Kersting, Adam R. Kosiorek:
Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation. CoRR abs/2104.01148 (2021) - [i75]Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer, Tim Grube, Kristian Kersting, Max Mühlhäuser:
User Label Leakage from Gradients in Federated Learning. CoRR abs/2105.09369 (2021) - [i74]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Intriguing Parameters of Structural Causal Models. CoRR abs/2105.12697 (2021) - [i73]Nils Thoma, Zhongjie Yu, Fabrizio Ventola, Kristian Kersting:
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting. CoRR abs/2106.04148 (2021) - [i72]Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting:
Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression. CoRR abs/2106.08687 (2021) - [i71]Maximilian Otte, Quentin Delfosse, Johannes Czech, Kristian Kersting:
Generative Adversarial Neural Cellular Automata. CoRR abs/2108.04328 (2021) - [i70]Matej Zecevic, Devendra Singh Dhami, Petar Velickovic, Kristian Kersting:
Relating Graph Neural Networks to Structural Causal Models. CoRR abs/2109.04173 (2021) - [i69]Steven Lang, Fabrizio Ventola, Kristian Kersting:
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection. CoRR abs/2109.06148 (2021) - [i68]Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting:
Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits. CoRR abs/2109.06587 (2021) - [i67]Patrick Schramowski, Felix Friedrich, Christopher Tauchmann, Kristian Kersting:
Interactively Generating Explanations for Transformer Language Models. CoRR abs/2110.02058 (2021) - [i66]Matej Zecevic, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting:
Structural Causal Interpretation Theorem. CoRR abs/2110.02395 (2021) - [i65]Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting:
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability. CoRR abs/2110.03331 (2021) - [i64]Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming. CoRR abs/2110.03395 (2021) - [i63]Patrick Schramowski, Kristian Kersting:
Inferring Offensiveness In Images From Natural Language Supervision. CoRR abs/2110.04222 (2021) - [i62]Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Neuro-Symbolic Forward Reasoning. CoRR abs/2110.09383 (2021) - [i61]Athresh Karanam, Saurabh Mathur, Predrag Radivojac, Kristian Kersting, Sriraam Natarajan:
Explaining Deep Tractable Probabilistic Models: The sum-product network case. CoRR abs/2110.09778 (2021) - [i60]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
On the Tractability of Neural Causal Inference. CoRR abs/2110.12052 (2021) - [i59]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
The Causal Loss: Driving Correlation to Imply Causation. CoRR abs/2110.12066 (2021) - [i58]Lukas Struppek, Dominik Hintersdorf, Daniel Neider, Kristian Kersting:
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash. CoRR abs/2111.06628 (2021) - [i57]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
Do Not Trust Prediction Scores for Membership Inference Attacks. CoRR abs/2111.09076 (2021) - [i56]Wolfgang Stammer, Marius Memmel, Patrick Schramowski, Kristian Kersting:
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. CoRR abs/2112.02290 (2021) - 2020
- [j55]Xiaoting Shao, Tjitze Rienstra, Matthias Thimm, Kristian Kersting:
Towards Understanding and Arguing with Classifiers: Recent Progress. Datenbank-Spektrum 20(2): 171-180 (2020) - [j54]Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz:
Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data. Frontiers Artif. Intell. 3: 24 (2020) - [j53]Patrick Schramowski, Cigdem Turan, Sophie F. Jentzsch, Constantin A. Rothkopf, Kristian Kersting:
The Moral Choice Machine. Frontiers Artif. Intell. 3: 36 (2020) - [j52]Rudolf Lioutikov, Guilherme Maeda, Filipe Veiga, Kristian Kersting, Jan Peters:
Learning attribute grammars for movement primitive sequencing. Int. J. Robotics Res. 39(1) (2020) - [j51]Rafet Sifa, Raheel Yawar, Rajkumar Ramamurthy, Christian Bauckhage, Kristian Kersting:
Matrix- and Tensor Factorization for Game Content Recommendation. Künstliche Intell. 34(1): 57-67 (2020) - [j50]Kristian Kersting:
Rethinking Computer Science Through AI. Künstliche Intell. 34(4): 435-437 (2020) - [j49]Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Franziska Herbert, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting:
Making deep neural networks right for the right scientific reasons by interacting with their explanations. Nat. Mach. Intell. 2(8): 476-486 (2020) - [j48]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig:
DeepDB: Learn from Data, not from Queries! Proc. VLDB Endow. 13(7): 992-1005 (2020) - [c175]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Expanding PPML beyond Neural Networks. PPMLP@CCS 2020: 9-14 - [c174]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Privacy-Preserving Sum-Product Network Inference. ECAI 2020: 1946-1953 - [c173]Ute Schmid, Volker Tresp, Matthias Bethge, Kristian Kersting, Rainer Stiefelhagen:
Künstliche Intelligenz - Die dritte Welle. GI-Jahrestagung 2020: 91-95 - [c172]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. ICLR 2020 - [c171]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020 - [c170]Cigdem Turan, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Alfie: An Interactive Robot with Moral Compass. ICMI 2020: 758-759 - [c169]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML 2020: 7563-7574 - [c168]Matej Petkovic, Michelangelo Ceci, Kristian Kersting, Saso Dzeroski:
Estimating the Importance of Relational Features by Using Gradient Boosting. ISMIS 2020: 362-371 - [c167]Tjitze Rienstra, Matthias Thimm, Kristian Kersting, Xiaoting Shao:
Independence and D-separation in Abstract Argumentation. KR 2020: 713-722 - [c166]Kristian Kersting:
On Hybrid and Systems AI. LWDA 2020: 3 - [c165]