متابعة
Kristian Kersting
Kristian Kersting
Professor of AI & ML, Technical University of Darmstadt, Hessian.ai/DFKI, CAIRNE/ELLIS, AAAI Fellow
بريد إلكتروني تم التحقق منه على cs.tu-darmstadt.de - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
TUDataset: A collection of benchmark datasets for learning with graphs‏
MN Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting ...‏
ICML 2020 Workshop on Graph Representation Learning and Beyond (GRL+ 2020), 2020‏
1278*2020
Probabilistic Inductive Logic Programming‏
L De Raedt, K Kersting‏
Probabilistic Inductive Logic Programming - Theory and Applications, 1-27, 2008‏
5052008
Most likely heteroscedastic Gaussian process regression‏
K Kersting, C Plagemann, P Pfaff, W Burgard‏
Proceedings of the 24th international conference on Machine learning, 393-400, 2007‏
4732007
Statistical relational artificial intelligence: Logic, probability, and computation‏
L De Raedt, K Kersting, S Natarajan, D Poole‏
Springer Nature, 2022‏
401*2022
Adaptive Bayesian logic programs‏
K Kersting, L De Raedt‏
International Conference on Inductive Logic Programming, 104-117, 2001‏
3922001
Large pre-trained language models contain human-like biases of what is right and wrong to do‏
P Schramowski, C Turan, N Andersen, CA Rothkopf, K Kersting‏
Nature Machine Intelligence 4 (3), 258-268, 2022‏
3342022
Propagation kernels: efficient graph kernels from propagated information‏
M Neumann, R Garnett, C Bauckhage, K Kersting‏
Machine learning 102, 209-245, 2016‏
3192016
DeepDB: Learn from Data, not from Queries!‏
B Hilprecht, A Schmidt, M Kulessa, A Molina, K Kersting, C Binnig‏
PVLDB 13 (7), 2020‏
3112020
Explanatory Interactive Machine Learning‏
S Teso, K Kersting‏
Proceedings of the 2nd AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2019‏
2702019
Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models‏
P Schramowski, M Brack, B Deiseroth, K Kersting‏
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023‏
2642023
Making deep neural networks right for the right scientific reasons by interacting with their explanations‏
P Schramowski, W Stammer, S Teso, A Brugger, F Herbert, X Shao, ...‏
Nature Machine Intelligence 2 (8), 476-486, 2020‏
2642020
Lifted Probabilistic Inference with Counting Formulas.‏
B Milch, LS Zettlemoyer, K Kersting, M Haimes, LP Kaelbling‏
AAAI 8, 1062-1068, 2008‏
2502008
Predicting player churn in the wild‏
F Hadiji, R Sifa, A Drachen, C Thurau, K Kersting, C Bauckhage‏
2014 ieee conference on computational intelligence and games, 1-8, 2014‏
2412014
Bayesian Logic Programming: Theory and Tool‏
K Kersting, L De Raedt‏
Introduction to Statistical Relational Learning, 291, 2007‏
2292007
Probabilistic logic learning‏
L De Raedt, K Kersting‏
ACM SIGKDD Explorations Newsletter 5 (1), 31-48, 2003‏
2272003
Towards combining inductive logic programming with Bayesian networks‏
K Kersting, L De Raedt‏
International Conference on Inductive Logic Programming, 118-131, 2001‏
2052001
Hyperspectral phenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions‏
M Kuska, M Wahabzada, M Leucker, HW Dehne, K Kersting, EC Oerke, ...‏
Plant methods 11, 1-15, 2015‏
2032015
Counting belief propagation‏
K Kersting, B Ahmadi, S Natarajan‏
arXiv preprint arXiv:1205.2637, 2012‏
2022012
Gradient-based boosting for statistical relational learning: The relational dependency network case‏
S Natarajan, T Khot, K Kersting, B Gutmann, J Shavlik‏
Machine Learning 86, 25-56, 2012‏
1952012
Introduction to statistical relational learning‏
D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ...‏
MIT press, 2007‏
1852007
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مقالات 1–20