Patrick Jähnichen
Patrick Jähnichen
PostDoc in Machine Learning, Humboldt-Universität zu Berlin
Verified email at - Homepage
Cited by
Cited by
Exploring issues in a networked public sphere: Combining hyperlink network analysis and topic modeling
D Maier, A Waldherr, P Miltner, P Jähnichen, B Pfetsch
Social Science Computer Review, 1-18, 2017
Matching results of latent dirichlet allocation for text
A Niekler, P Jähnichen
Proceedings of ICCM, 317-322, 2012
Scalable Generalized Dynamic Topic Models
P Jähnichen, F Wenzel, M Kloft, S Mandt
arXiv preprint arXiv:1803.07868, 2018
Cross-modal Hallucination for Few-shot Fine-grained Recognition
F Pahde, P Jähnichen, T Klein, M Nabi
arXiv preprint arXiv:1806.05147, 2018
Mining Big Data With Computational Methods
A Waldherr, G Heyer, P Jähnichen, A Niekler, G Wiedemann
Political Communication in the Online World: Theoretical Approaches and …, 2015
Exploratory search through interactive visualization of topic models
P Jähnichen, P Oesterling, T Liebmann, G Heyer, C Kuras, ...
Proceedings of the Digital Humanities 6 (8), 13, 2015
Exploratory search through visual analysis of topic models
P Jähnichen, P Oesterling, G Heyer, T Liebmann, G Scheuermann, ...
Digital Humanities Quarterly (special issue), 2015
Time Dynamic Topic Models
P Jähnichen
ASV Monitor: Creating comparability of machine learning methods for content analysis
A Niekler, P Jähnichen, G Heyer
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
Classification using Logistic Regression
I Schuster, P Jähnichen
Universität Lepzig, 2012
Finding and Analyzing Social Networks in unstructured web log data using probabilistic topic modeling
P Jähnichen, G Heyer
Master’s thesis, 2009
Topics in Social Media for Disaster Management-A German Case Study on the Flood 2013
A Schlaf, S Gründer-Fahrer, P Jähnichen
Proc. EMOT workshop on LREC 2016, 17-24, 2016
Topological visual analysis of clusterings in high-dimensional information spaces
P Oesterling, P Jähnichen, G Heyer, G Scheuermann
it-Information Technology 57 (1), 3-10, 2015
Scalable Inference in Dynamic Mixture Models
P Jähnichen, F Wenzel, M Kloft
Generalizing and Scaling up Dynamic Topic Models via Inducing Point Variational Inference
P Jähnichen, F Wenzel, M Kloft, S Mandt
NIPS 2017 Workshop on Advances in Approximate Bayesian Inference, 2017
Predicting social networks in weblogs
P Jähnichen
11th International Conference on Innovative Internet Community Systems (I2CS …, 2011
Learning to Remember what to Remember: A Synaptic Plasticity Driven Framework
O Ostapenko, M Puscas, T Klein, P Jähnichen, M Nabi
The Praxis of Social Knowledge Federation
A Bleier, P Jähnichen, U Schulze, L Maicher
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