Segui
Manuel Haussmann
Titolo
Citata da
Citata da
Anno
Deep-learning jets with uncertainties and more
S Bollweg, M Haußmann, G Kasieczka, M Luchmann, T Plehn, ...
SciPost Physics 8 (1), 006, 2020
692020
Understanding event-generation networks via uncertainties
M Bellagente, M Haußmann, M Luchmann, T Plehn
SciPost Physics 13 (1), 003, 2022
612022
Deep Active Learning with Adaptive Acquisition
M Haußmann, FA Hamprecht, M Kandemir
International Joint Conference on Artificial Intelligence (IJCAI), arXiv …, 2019
522019
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
432017
Sampling-free variational inference of bayesian neural networks by variance backpropagation
M Haußmann, FA Hamprecht, M Kandemir
Uncertainty in Artificial Intelligence, 563-573, 2020
372020
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
232021
Variational Weakly Supervised Gaussian Processes.
M Kandemir, M Haussmann, F Diego, KT Rajamani, J Van Der Laak, ...
BMVC, 71.1-71.12, 2016
162016
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
132019
Evidential turing processes
M Kandemir, A Akgül, M Haussmann, G Unal
International Conference on Learning Representations; arXiv preprint arXiv …, 2021
82021
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
62024
PAC-Bayesian soft actor-critic learning
B Tasdighi, A Akgül, M Haussmann, KK Brink, M Kandemir
Advances in Approximate Bayesian Inference Symposium, 2024
52024
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
42023
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
A Akgül, M Haußmann, M Kandemir
Conference on Neural Information Processing Systems, 2024
12024
Estimating treatment effects from single-arm trials via latent-variable modeling
M Haussmann, TMS Le, V Halla-aho, S Kurki, J Leinonen, M Koskinen, ...
International Conference on Artificial Intelligence and Statistics, 2926-2934, 2024
12024
Accurate Surrogate Amplitudes with Calibrated Uncertainties
H Bahl, N Elmer, L Favaro, M Haußmann, T Plehn, R Winterhalder
arXiv preprint arXiv:2412.12069, 2024
2024
Latent mixed-effect models for high-dimensional longitudinal data
P Ong, M Haußmann, O Lönnroth, H Lähdesmäki
arXiv preprint arXiv:2409.11008, 2024
2024
Latent variable model for high-dimensional point process with structured missingness
M Sinelnikov, M Haussmann, H Lähdesmäki
Forty-first International Conference on Machine Learning., 2024
2024
Deep Exploration with PAC-Bayes
B Tasdighi, M Haussmann, N Werge, YS Wu, M Kandemir
arXiv preprint arXiv:2402.03055, 2024
2024
Learning high-dimensional mixed models via amortized variational inference
P Ong, M Haussmann, H Lähdesmäki
ICML 2024 Workshop on Structured Probabilistic Inference {\&} Generative …, 2024
2024
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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