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2020 – today
- 2023
[c3]Simon Damm
, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke:
The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS 2023: 3931-3960- 2022
- [j3]Florian Hirschberger, Dennis Forster, Jörg Lücke:
A Variational EM Acceleration for Efficient Clustering at Very Large Scales. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9787-9801 (2022) - 2020
- [i4]Jörg Lücke, Dennis Forster, Zhenwen Dai:
The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies. CoRR abs/2010.14860 (2020)
2010 – 2019
- 2019
- [j2]Jörg Lücke, Dennis Forster:
k-means as a variational EM approximation of Gaussian mixture models. Pattern Recognit. Lett. 125: 349-356 (2019) - 2018
- [j1]Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke:
Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks. Neural Comput. 30(8) (2018) - [c2]Dennis Forster, Jörg Lücke:
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means. AISTATS 2018: 124-132 - [i3]Florian Hirschberger, Dennis Forster, Jörg Lücke:
Accelerated Training of Large-Scale Gaussian Mixtures by a Merger of Sublinear Approaches. CoRR abs/1810.00803 (2018) - 2017
- [c1]Dennis Forster, Jörg Lücke:
Truncated variational EM for semi-supervised neural simpletrons. IJCNN 2017: 3769-3776 - [i2]Dennis Forster, Jörg Lücke:
Truncated Variational EM for Semi-Supervised Neural Simpletrons. CoRR abs/1702.01997 (2017) - 2015
- [i1]Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke:
Neural Simpletrons - Minimalistic Probabilistic Networks for Learning With Few Labels. CoRR abs/1506.08448 (2015)
Coauthor Index
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