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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
- 2022
[j61]Parisa Kordjamshidi, Dan Roth, Kristian Kersting:
Declarative Learning-Based Programming as an Interface to AI Systems. Frontiers Artif. Intell. 5: 755361 (2022)- [j60]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) - [j59]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) - [c183]Lukas Struppek, Dominik Hintersdorf, Daniel Neider, Kristian Kersting:
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash. FAccT 2022: 58-69 - [c182]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 - [c181]Mina Ameli, Viktor Pfanschilling, Anar Amirli, Wolfgang Maaß, Kristian Kersting:
Unsupervised Multi-sensor Anomaly Localization with Explainable AI. AIAI (1) 2022: 507-519 - [i92]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) - [i91]Xiaoting Shao, Karl Stelzner, Kristian Kersting:
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. CoRR abs/2202.00391 (2022) - [i90]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) - [i89]Xuan Xie, Kristian Kersting, Daniel Neider:
Neuro-Symbolic Verification of Deep Neural Networks. CoRR abs/2203.00938 (2022) - [i88]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
A Typology to Explore and Guide Explanatory Interactive Machine Learning. CoRR abs/2203.03668 (2022) - [i87]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) - [i86]Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting:
Finding Structure and Causality in Linear Programs. CoRR abs/2203.15274 (2022) - [i85]Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting, Iryna Gurevych:
Adaptable Adapters. CoRR abs/2205.01549 (2022) - [i84]Xiaoting Shao, Kristian Kersting:
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models. CoRR abs/2205.07774 (2022) - [i83]David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Machines Explaining Linear Programs. CoRR abs/2206.07194 (2022) - [i82]Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation. CoRR abs/2206.07195 (2022) - [i81]Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Towards a Solution to Bongard Problems: A Causal Approach. CoRR abs/2206.07196 (2022) - [i80]Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami:
Attributions Beyond Neural Networks: The Linear Program Case. CoRR abs/2206.07203 (2022) - 2021
- [j58]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahareh 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) - [j57]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) - [j56]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) - [j55]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) - [c180]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 - [c179]Johannes Czech, Patrick Korus, Kristian Kersting:
Improving AlphaZero Using Monte-Carlo Graph Search. ICAPS 2021: 103-111 - [c178]Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations. CVPR 2021: 3619-3629 - [c177]Zhongjie Yu, Fabrizio G. Ventola, Kristian Kersting:
Whittle Networks: A Deep Likelihood Model for Time Series. ICML 2021: 12177-12186 - [c176]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 - [c175]Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting:
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP 2021: 251-265 - [c174]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 - [c173]Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting:
Leveraging probabilistic circuits for nonparametric multi-output regression. UAI 2021: 2008-2018 - [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 I. Lecture Notes in Computer Science 12457, Springer 2021, ISBN 978-3-030-67657-5 [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 II. Lecture Notes in Computer Science 12458, Springer 2021, ISBN 978-3-030-67660-5 [contents] - [e10]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
- [j54]Xiaoting Shao, Tjitze Rienstra, Matthias Thimm, Kristian Kersting:
Towards Understanding and Arguing with Classifiers: Recent Progress. Datenbank-Spektrum 20(2): 171-180 (2020) - [j53]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) - [j52]Patrick Schramowski, Cigdem Turan, Sophie F. Jentzsch, Constantin A. Rothkopf, Kristian Kersting:
The Moral Choice Machine. Frontiers Artif. Intell. 3: 36 (2020) - [j51]Rudolf Lioutikov, Guilherme Maeda, Filipe Veiga, Kristian Kersting, Jan Peters:
Learning attribute grammars for movement primitive sequencing. Int. J. Robotics Res. 39(1) (2020) - [j50]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) - [j49]Kristian Kersting:
Rethinking Computer Science Through AI. Künstliche Intell. 34(4): 435-437 (2020) - [j48]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) - [j47]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) - [c172]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Expanding PPML beyond Neural Networks. PPMLP@CCS 2020: 9-14 - [c171]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Privacy-Preserving Sum-Product Network Inference. ECAI 2020: 1946-1953 - [c170]Ute Schmid, Volker Tresp, Matthias Bethge, Kristian Kersting, Rainer Stiefelhagen:
Künstliche Intelligenz - Die dritte Welle. GI-Jahrestagung 2020: 91-95 - [c169]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. ICLR 2020 - [c168]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020 - [c167]Cigdem Turan, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Alfie: An Interactive Robot with Moral Compass. ICMI 2020: 758-759 - [c166]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 - [c165]Matej Petkovic, Michelangelo Ceci, Kristian Kersting, Saso Dzeroski:
Estimating the Importance of Relational Features by Using Gradient Boosting. ISMIS 2020: 362-371 - [c164]Tjitze Rienstra, Matthias Thimm, Kristian Kersting, Xiaoting Shao:
Independence and D-separation in Abstract Argumentation. KR 2020: 713-722 - [c163]Kristian Kersting:
On Hybrid and Systems AI. LWDA 2020: 3 - [c162]Nandini Ramanan, Mayukh Das, Kristian Kersting, Sriraam Natarajan:
Discriminative Non-Parametric Learning of Arithmetic Circuits. PGM 2020: 353-364 - [c161]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM 2020: 401-412 - [c160]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Residual Sum-Product Networks. PGM 2020: 545-556 - [c159]Xiaoting Shao, Zhongjie Yu, Arseny Skryagin, Tjitze Rienstra, Matthias Thimm, Kristian Kersting:
Modelling Multivariate Ranking Functions with Min-Sum Networks. SUM 2020: 281-288 - [i55]Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting:
Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations. CoRR abs/2001.05371 (2020) - [i54]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Privacy-preserving Sum-Product Network Inference. CoRR abs/2002.00801 (2020) - [i53]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. CoRR abs/2004.06231 (2020) - [i52]Srijita Das, Sriraam Natarajan, Kaushik Roy, Ronald Parr, Kristian Kersting:
Fitted Q-Learning for Relational Domains. CoRR abs/2006.05595 (2020) - [i51]Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann:
TUDataset: A collection of benchmark datasets for learning with graphs. CoRR abs/2007.08663 (2020) - [i50]Cigdem Turan, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Alfie: An Interactive Robot with a Moral Compass. CoRR abs/2009.05349 (2020) - [i49]Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations. CoRR abs/2011.12854 (2020) - [i48]Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer:
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation. CoRR abs/2012.08459 (2020) - [i47]Johannes Czech, Patrick Korus, Kristian Kersting:
Monte-Carlo Graph Search for AlphaZero. CoRR abs/2012.11045 (2020) - [i46]Kristian Kersting, Miryung Kim, Guy Van den Broeck, Thomas Zimmermann:
SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091). Dagstuhl Reports 10(2): 76-87 (2020)
2010 – 2019
- 2019
- [j46]Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt:
Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach. Auton. Robots 43(6): 1393-1418 (2019) - [j45]Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel:
A unifying view of explicit and implicit feature maps of graph kernels. Data Min. Knowl. Discov. 33(6): 1505-1547 (2019) - [j44]Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni:
Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning. Frontiers Big Data 2: 52 (2019) - [j43]Fabrizio Riguzzi, Kristian Kersting, Marco Lippi, Sriraam Natarajan:
Editorial: Statistical Relational Artificial Intelligence. Frontiers Robotics AI 6: 68 (2019) - [j42]Anna Brugger, Jan Behmann, Stefan Paulus, Hans-Georg Luigs, Matheus Thomas Kuska, Patrick Schramowski, Kristian Kersting, Ulrike Steiner, Anne-Katrin Mahlein:
Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range. Remote. Sens. 11(12): 1401 (2019) - [c158]Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. AAAI 2019: 5207-5215 - [c157]Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan:
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. AAAI 2019: 7816-7824 - [c156]Sophie F. Jentzsch, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices. AIES 2019: 37-44 - [c155]Stefano Teso, Kristian Kersting:
Explanatory Interactive Machine Learning. AIES 2019: 239-245 - [c154]Lukas Weber, Lukas Sommer, Julian Oppermann, Alejandro Molina, Kristian Kersting, Andreas Koch:
Resource-Efficient Logarithmic Number Scale Arithmetic for SPN Inference on FPGAs. FPT 2019: 251-254 - [c153]Karl Stelzner, Robert Peharz, Kristian Kersting:
Faster Attend-Infer-Repeat with Tractable Probabilistic Models. ICML 2019: 5966-5975 - [c152]Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan:
Neural Networks for Relational Data. ILP 2019: 62-71 - [c151]Stefan Lüdtke, Alejandro Molina, Kristian Kersting, Thomas Kirste:
Gaussian Lifted Marginal Filtering. KI 2019: 230-243 - [c150]Claas Völcker, Alejandro Molina, Johannes Neumann, Dirk Westermann, Kristian Kersting:
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets. PKDD/ECML Workshops (1) 2019: 28-43 - [c149]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani:
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI 2019: 334-344 - [i45]Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting:
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR abs/1901.03704 (2019) - [i44]Kristian Kersting, Jan Peters, Constantin A. Rothkopf:
Was ist eine Professur fuer Kuenstliche Intelligenz? CoRR abs/1903.09516 (2019) - [i43]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR abs/1905.08550 (2019) - [i42]Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni:
Neural-Symbolic Argumentation Mining: an Argument in Favour of Deep Learning and Reasoning. CoRR abs/1905.09103 (2019) - [i41]Parisa Kordjamshidi, Dan Roth, Kristian Kersting:
Declarative Learning-Based Programming as an Interface to AI Systems. CoRR abs/1906.07809 (2019) - [i40]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. CoRR abs/1907.06732 (2019) - [i39]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Random Sum-Product Forests with Residual Links. CoRR abs/1908.03250 (2019) - [i38]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. CoRR abs/1908.06660 (2019) - [i37]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig:
DeepDB: Learn from Data, not from Queries! CoRR abs/1909.00607 (2019) - [i36]Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan:
Neural Networks for Relational Data. CoRR abs/1909.04723 (2019) - [i35]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. CoRR abs/1910.02425 (2019) - [i34]Patrick Schramowski, Cigdem Turan, Sophie F. Jentzsch, Constantin A. Rothkopf, Kristian Kersting:
BERT has a Moral Compass: Improvements of ethical and moral values of machines. CoRR abs/1912.05238 (2019) - [i33]Michael Benedikt, Kristian Kersting, Phokion G. Kolaitis, Daniel Neider:
Logic and Learning (Dagstuhl Seminar 19361). Dagstuhl Reports 9(9): 1-22 (2019) - 2018
- [j41]Kristian Kersting:
Machine Learning and Artificial Intelligence: Two Fellow Travelers on the Quest for Intelligent Behavior in Machines. Frontiers Big Data 1: 6 (2018) - [j40]