Martin Trapp

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Robert PeharzAssistant Professor of AI, TU GrazVerified email at tugraz.at
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Arno SolinAssistant Professor in Machine Learning, Aalto UniversityVerified email at aalto.fi
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Antonio VergariReader (Associate Professor), University of Edinburgh, UKVerified email at ed.ac.uk
Franz PernkopfGraz University of TechnologyVerified email at tugraz.at
Hong GeCambridge UniversityVerified email at cam.ac.uk
Andrea PilzerSA, NVIDIA AI Technology Center ItalyVerified email at nvidia.com
Dietmar SchabusVeritoneVerified email at veritone.com
Kai XuResearch Scientist, MIT-IBM Watson AI LabVerified email at mit.edu
Stephanie GrossAustrian Research Institute for Artificial IntelligenceVerified email at ofai.at
Lassi MeronenPhD studentVerified email at aalto.fi
Katja BühlerScientific Director, VRVis Research Center, ViennaVerified email at vrvis.at
Subhankar RoyVerified email at unitn.it
Zhongjie YuTU DarmstadtVerified email at cs.tu-darmstadt.de
Ella TamirPhD student, Aalto UniversityVerified email at aalto.fi
Martin ANDRAUDAssistant Professor (UCLouvain) & Visiting Prof. (Aalto University)Verified email at uclouvain.be
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
David MajorResearcher, Biomedical Image Informatics, VRVis Research CenterVerified email at vrvis.at
Marcus KlassonPostdoctoral Researcher, Aalto UniversityVerified email at aalto.fi

Martin Trapp

Machine learning researcher, Aalto University

Verified email at aalto.fi - Homepage

Probabilistic Machine Learning Bayesian Deep Learning Tractable Probabilistic Inference


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Random sum-product networks: A simple and effective approach to probabilistic deep learning R Peharz, A Vergari, K Stelzner, A Molina, X Shao, M Trapp, K Kersting, ... Uncertainty in Artificial Intelligence, 334-344, 2020	160*	2020
Einsum networks: Fast and scalable learning of tractable probabilistic circuits R Peharz, S Lang, A Vergari, K Stelzner, A Molina, M Trapp, ... International Conference on Machine Learning, 7563-7574, 2020	123	2020
One million posts: A data set of german online discussions D Schabus, M Skowron, M Trapp Proceedings of the 40th international ACM SIGIR conference on research and …, 2017	66	2017
Uncertainty-guided source-free domain adaptation S Roy, M Trapp, A Pilzer, J Kannala, N Sebe, E Ricci, A Solin European conference on computer vision, 537-555, 2022	60	2022
Bayesian learning of sum-product networks M Trapp, R Peharz, H Ge, F Pernkopf, Z Ghahramani Advances in Neural Information Processing Systems (NeurIPS), 2019	53	2019
Deep Structured Mixtures of Gaussian Processes M Trapp, R Peharz, F Pernkopf, CE Rasmussen International Conference on Artificial Intelligence and Statistics (AISTATS), 2020	49*	2020
AdvancedHMC. jl: A robust, modular and efficient implementation of advanced HMC algorithms K Xu, H Ge, W Tebbutt, M Tarek, M Trapp, Z Ghahramani Symposium on Advances in Approximate Bayesian Inference, 1-10, 2020	24	2020
Periodic activation functions induce stationarity L Meronen, M Trapp, A Solin Advances in Neural Information Processing Systems 34, 1673-1685, 2021	21	2021
Safe Semi-Supervised Learning of Sum-Product Networks M Trapp, T Madl, R Peharz, F Pernkopf, R Trappl Conference on Uncertainty in Artificial Intelligence (UAI), 2017	17	2017
Automatic identification of character types from film dialogs M Skowron, M Trapp, S Payr, R Trappl Applied Artificial Intelligence 30 (10), 942-973, 2016	16	2016
Structure inference in sum-product networks using infinite sum-product trees M Trapp, R Peharz, M Skowron, T Madl, F Pernkopf, R Trappl NIPS Workshop on Practical Bayesian Nonparametrics, 2016	16	2016
Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression Z Yu, M Zhu, M Trapp, A Skryagin, K Kersting Conference on Uncertainty in Artificial Intelligence (UAI), 2021	14	2021
Fixing overconfidence in dynamic neural networks L Meronen, M Trapp, A Pilzer, L Yang, A Solin IEEE/CVF Winter Conference on Applications of Computer Vision, 2680-2690, 2024	11	2024
Sum-product-transform networks: Exploiting symmetries using invertible transformations T Pevný, V Smídl, M Trapp, O Poláček, T Oberhuber International Conference on Probabilistic Graphical Models, 341-352, 2020	11	2020
DynamicPPL: Stan-like speed for dynamic probabilistic models M Tarek, K Xu, M Trapp, H Ge, Z Ghahramani arXiv preprint arXiv:2002.02702, 2020	10	2020
Grounded word learning on a pepper robot M Hirschmanner, S Gross, B Krenn, F Neubarth, M Trapp, M Vincze Proceedings of the 18th International Conference on Intelligent Virtual …, 2018	9	2018
Transport with Support: Data-Conditional Diffusion Bridges E Tamir, M Trapp, A Solin Transactions on Machine Learning Research (TMLR), 2023	8	2023
Subtractive Mixture Models via Squaring: Representation and Learning L Loconte, AM Sladek, S Mengel, M Trapp, A Solin, N Gillis, A Vergari arXiv preprint arXiv:2310.00724, 2023	8	2023
Characteristic Circuits Z Yu, M Trapp, K Kersting Advances in Neural Information Processing Systems 36, 2024	5	2024
Disentangling model multiplicity in deep learning A Heljakka, M Trapp, J Kannala, A Solin arXiv preprint arXiv:2206.08890, 2022	5*	2022

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