Follow
Manuel Haussmann
Title
Cited by
Cited by
Year
Deep-learning jets with uncertainties and more
S Bollweg, M Haußmann, G Kasieczka, M Luchmann, T Plehn, ...
SciPost Physics 8 (1), 006, 2020
562020
Deep Active Learning with Adaptive Acquisition
M Haußmann, FA Hamprecht, M Kandemir
International Joint Conference on Artificial Intelligence (IJCAI), arXiv …, 2019
432019
Understanding event-generation networks via uncertainties
M Bellagente, M Haußmann, M Luchmann, T Plehn
SciPost Physics 13 (1), 003, 2022
42*2022
Variational Bayesian Multiple Instance Learning with Gaussian Processes
M Haußmann, FA Hamprecht, M Kandemir
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 6570-6579, 2017
342017
Sampling-free variational inference of bayesian neural networks by variance backpropagation
M Haußmann, FA Hamprecht, M Kandemir
Uncertainty in Artificial Intelligence, 563-573, 2020
302020
Learning partially known stochastic dynamics with empirical PAC Bayes
M Haußmann, S Gerwinn, A Look, B Rakitsch, M Kandemir
International Conference on Artificial Intelligence and Statistics, 478-486, 2021
202021
Variational Weakly Supervised Gaussian Processes.
M Kandemir, M Haussmann, F Diego, KT Rajamani, J Van Der Laak, ...
BMVC, 71.1-71.12, 2016
152016
LeMoNADe: learned motif and neuronal assembly detection in calcium imaging videos
E Kirschbaum, M Haußmann, S Wolf, H Sonntag, J Schneider, S Elzoheiry, ...
International Conference on Learning Representations 2019, arXiv preprint …, 2018
142018
Bayesian Evidential Deep Learning with PAC Regularization
M Haussmann, S Gerwinn, M Kandemir
3rd Advances in Approximate Bayesian Inference (AABI) Symposium, arXiv …, 2019
102019
Evidential turing processes
M Kandemir, A Akgül, M Haussmann, G Unal
arXiv preprint arXiv:2106.01216, 2021
62021
Latent variable model for high-dimensional point process with structured missingness
M Sinelnikov, M Haussmann, H Lähdesmäki
arXiv preprint arXiv:2402.05758, 2024
2024
A comparative study of clinical trial and real-world data in patients with diabetic kidney disease
S Kurki, V Halla-Aho, M Haussmann, H Lähdesmäki, JV Leinonen, ...
Scientific Reports 14 (1), 1731, 2024
2024
Practical Equivariances via Relational Conditional Neural Processes
D Huang, M Haussmann, U Remes, ST John, G Clarté, K Luck, S Kaski, ...
Advances in Neural Information Processing Systems 36, 29201-29238, 2023
2023
Estimating treatment effects from single-arm trials via latent-variable modeling
M Haussmann, TMS Le, V Halla-aho, S Kurki, J Leinonen, M Koskinen, ...
arXiv preprint arXiv:2311.03002, 2023
2023
Control and monitoring of physical system based on trained Bayesian neural network
M Kandemir, M Haussmann
US Patent 11,275,381, 2022
2022
Bayesian Neural Networks for Probabilistic Machine Learning
M Haußmann
2021
Supplementary Material for the Paper:” Variational Bayesian Multiple Instance Learning with Gaussian Processes”
M Haußmann, FA Hamprecht, M Kandemir
The system can't perform the operation now. Try again later.
Articles 1–17