Christian Donner
Christian Donner
Eidgenössische Technische Hochschule Zürich
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Cited by
Cited by
Efficient Bayesian inference of sigmoidal Gaussian Cox processes
C Donner, M Opper
The Journal of Machine Learning Research 19 (1), 2710-2743, 2018
Approximate inference for time-varying interactions and macroscopic dynamics of neural populations
C Donner, K Obermayer, H Shimazaki
PLoS computational biology 13 (1), e1005309, 2017
Multi-class gaussian process classification made conjugate: Efficient inference via data augmentation
T Galy-Fajou, F Wenzel, C Donner, M Opper
Uncertainty in artificial intelligence, 755-765, 2020
Extraction and segmentation of sputum cells for lung cancer early diagnosis
F Taher, N Werghi, H Al-Ahmad, C Donner
Algorithms 6 (3), 512-531, 2013
Inverse Ising problem in continuous time: A latent variable approach
C Donner, M Opper
Physical Review E 96 (6), 062104, 2017
GP-ETAS: Semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model
C Molkenthin, C Donner, S Reich, G Zöller, S Hainzl, M Holschneider, ...
Statistics and computing 32 (2), 29, 2022
Efficient bayesian inference for a gaussian process density model
C Donner, M Opper
arXiv preprint arXiv:1805.11494, 2018
Detection and segmentation of sputum cell for early lung cancer detection
N Werghi, C Donner, F Taher, H Al-Ahmad
2012 19th IEEE International Conference on Image Processing, 2813-2816, 2012
Segmentation of sputum cell image for early lung cancer detection
N Werghi, C Donner, F Taher, H Alahmad
IET Digital Library, 2012
Cell extraction from sputum images for early lung cancer detection
C Donner, N Werghi, F Taher, H Al-Ahmad
2012 16th IEEE Mediterranean Electrotechnical Conference, 485-488, 2012
Scalable multi-class Gaussian process classification via data augmentation
T Galy-Fajou, F Wenzel, C Donner, M Opper
Proc. NIPS Workshop Approx. Inference, 1-12, 2018
Generative inverse design of multimodal resonant structures for locally resonant metamaterials
S Dedoncker, C Donner, L Taenzer, B Van Damme
arXiv preprint arXiv:2309.04177, 2023
Optimization of resonant absorbers for passive vibration control: a numerical approach and its experimental validation
S Dedoncker, C Donner, L Taenzer, B Van Damme
Available at SSRN 4266071, 2022
Comparison of connectivity inference algorithms for classification of neuronal cultures using graph kernels
T Kim, P Hornauer, C Donner, A Hierlemann, K Borgwardt, M Schröter, ...
ECML PKDD Workshop on Machine Learning for Pharma and Healthcare …, 2020
Bayesian inference of inhomogeneous point process models
C Donner
PhD thesis, Technische Universität Berlin, 2019
Scalable logit gaussian process classification
F Wenzel, T Galy-Fajou, C Donner, M Kloft, M Opper
Advances in Approximate Bayesian Inference, NIPS Workshop, 2017
DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks
P Hornauer, G Prack, N Anastasi, S Ronchi, T Kim, C Donner, M Fiscella, ...
Stem Cell Reports 19 (2), 285-298, 2024
Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains
C Donner, J Bartram, P Hornauer, T Kim, D Roqueiro, A Hierlemann, ...
bioRxiv, 2024.02. 01.578336, 2024
A projected nonlinear state-space model for forecasting time series signals
C Donner, A Mishra, H Shimazaki
arXiv preprint arXiv:2311.13247, 2023
Modelling heteroscedasticity in state-space models
C Donner
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