36 Publikationen
2026 | Artikel | FH-PUB-ID: 6961
Lukassen, Fabian, et al. “From XAI to Stories: A Factorial Study of LLM-Generated Explanation Quality.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2601.02224.
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6960
Lukassen, Fabian, et al. “LLM-Augmented Change Point Detection: A Methodological Framework for Ensemble Detection and Automated Explanation.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2601.02957.
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6959
Schlee, Michael, et al. “LabelFusion: Fusing Large Language Models With Transformer Encoders for Robust Financial News Classification.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2512.10793.
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6958
Kumar, Manish, et al. “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2604.05635 .
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6957 | 
Amorin, Alvaro Paredes, et al. “Not All News Is Equal: Topic- and Event-Conditional Sentiment From Finetuned LLMs for Aluminum Price Forecasting.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2603.09085.
HSBI-PUB
| DOI
| Download (ext.)
2026 | Artikel | FH-PUB-ID: 6924 |
Berger, Ursula, et al. “Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung.” AStA Wirtschafts- und Sozialstatistisches Archiv, Springer, 2026, doi:10.1007/s11943-026-00372-0.
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| DOI
| Download (ext.)
2025 | Artikel | FH-PUB-ID: 6962 |
Amorin, Alvaro Paredes, et al. “Fine-Tuning of Lightweight Large Language Models for Sentiment Classification on Heterogeneous Financial Textual Data.” Preprint, Arxiv, 2025, doi:10.48550/arXiv.2512.00946.
HSBI-PUB
| DOI
| Download (ext.)
2025 | Konferenzbeitrag | FH-PUB-ID: 6966 |
Semnani, Parastoo, et al. From Prediction to Proposal in Catalysis: Robust Evaluation, LRP Explanations, and Relevance-Guided Candidate Generation. Openreview, 2025.
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2025 | Artikel | FH-PUB-ID: 6920
Reuter, Arik, et al. “Probabilistic Topic Modelling With Transformer Representations.” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 8, IEEE, 2025, pp. 14551–65, doi:10.1109/TNNLS.2025.3538262.
HSBI-PUB
| DOI
2025 | Artikel | FH-PUB-ID: 6919 |
Kant, Gillian, et al. “The Word and the Bullet: Out-Grouping and Threat Framing as Predictors of Islamic State Targeting, 2015-2020.” Terrorism and Political Violence, Taylor & Francis, 2025, doi:10.1080/09546553.2025.2561194.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 6942 |
Thielmann, Anton, et al. “Human in the Loop: How to Effectively Create Coherent Topics by Manually Labelling Only a Few Documents per Class.” Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), edited by Nicoletta Calzolari et al., Elra And Iccl, 2024, pp. 8395–405.
HSBI-PUB
| Download (ext.)
2024 | Artikel | FH-PUB-ID: 6963
Thielmann, Anton Frederik, et al. “Mambular: A Sequential Model for Tabular Deep Learning.” Preprint, Arxiv, 2024, doi:10.48550/arXiv.2408.06291.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 6964 |
Reuter, Arik, et al. “GPTopic: Dynamic and Interactive Topic Representations.” Preprint, Arxiv, 2024, doi:10.48550/arXiv.2403.03628.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Artikel | FH-PUB-ID: 6965
Stemmler, Henry, et al. “Solar Technology as a Shock-Coping Device: Evidence From Rural Tanzania.” Preprint, Ssrn, 2024, doi:10.2139/ssrn.5046518.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 6943 |
Kant, Gillian, et al. “One-Way Ticket to the Moon? An NLP-Based Insight on the Phenomenon of Small-Scale Neo-Broker Trading.” Social Network Analysis and Mining, vol. 14, 121, Springer, 2024, doi:10.1007/s13278-024-01273-2.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 6922
Thielmann, Anton Frederik, et al. “STREAM: Simplified Topic Retrieval, Exploration, and Analysis Module.” Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Volume 2: Short Papers, edited by Lun-Wei Ku et al., vol. 2, Association For Computational Linguistics, 2024, pp. 435–44, doi:10.18653/v1/2024.acl-short.41.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 6921 |
Semnani, Parastoo, et al. “A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery.” Journal of Physical Chemistry C, vol. 128, no. 50, 2024, pp. 21349–67, doi:10.1021/acs.jpcc.4c05332.
HSBI-PUB
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| Download (ext.)
2023 | Artikel | FH-PUB-ID: 6944 |
Weisser, Christoph, et al. “Pseudo-Document Simulation Method for Topic Model Evaluation on Short and Sparse Text Using Twitter Data.” Computational Statistics, vol. 38, no. 4, Springer, 2023, pp. 647–74, doi:10.1007/s00180-022-01246-z.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Artikel | FH-PUB-ID: 6967 |
Buchmüller, Andreas, et al. “Twitmo: A Twitter Data Topic Modeling and Visualization Package for R.” Preprint, Arxiv, 2022, doi:10.48550/arXiv.2207.11236.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Konferenzbeitrag | FH-PUB-ID: 6945
Tillmann, Arne, et al. “Privacy Estimation on Twitter: Modelling the Effect of Latent Topics on Privacy by Integrating XGBoost, Topic and Generalized Additive Models.” Proceedings of the 2022 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles, IoP, & SCI, edited by The Institute of Electrical and Electronics Engineers, Inc., Ieee, 2022, pp. 2325–32, doi:10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00365.
HSBI-PUB
| DOI
2022 | Artikel | FH-PUB-ID: 6946 |
Seufert, Jacqueline D., et al. “Mapping Ex-Ante Risks of COVID-19 in Indonesia Using a Bayesian Geostatistical Model on Airport Network Data.” Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 185, no. 4, Oxford University Press / Wiley, 2022, pp. 2121–55, doi:10.1111/rssa.12866.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Artikel | FH-PUB-ID: 6947 |
Kant, Gillian, et al. “Iterative Topic Model Filtering to Detect Conspiracy Theories on Twitter.” International Journal of Data Science and Analytics, Springer, 2022, doi:10.1007/s41060-022-00321-4.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Buchbeitrag | FH-PUB-ID: 6948
Kant, Gillian, et al. “Topic Model-Machine Learning Classifier Integrations on Geocoded Twitter Data.” Biomedical and Other Applications of Soft Computing, edited by Nguyen Hoang Phuong and Vladik Kreinovich, Springer, 2022, doi:10.1007/978-3-031-08580-2_11.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6968 |
Luber, Mattias, et al. “Community Detection via Hashtag-Graphs for Semi-Supervised NMF Topic Models.” Preprint, Arxiv, 2021, doi:10.48550/arXiv.2111.10401.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Buch als Herausgeber | FH-PUB-ID: 6970 |
Kruse , René-Marcel, et al., editors. Learning Deep Textwork: Perspectives on Natural Language Processing and Artificial Intelligence. Göttingen University Press, 2021, doi:10.17875/gup2021-1608.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Artikel | FH-PUB-ID: 6955 |
Thormann, Marah-Lisanne, et al. “Stock Price Predictions With LSTM Neural Networks and Twitter Sentiment.” Statistics, Optimization & Information Computing, vol. 9, no. 2, International Academic Press, 2021, pp. 268–87, doi:10.19139/soic-2310-5070-1202.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Konferenzbeitrag | FH-PUB-ID: 6951
Luber, Mattias, et al. “Identifying Topical Shifts in Twitter Streams: An Integration of Non-Negative Matrix Factorisation, Sentiment Analysis, and Structural Break Models for Large-Scale Data.” Disinformation in Open Online Media. MISDOOM 2021, edited by Jonathan Bright et al., Springer, 2021, pp. 33–49, doi:10.1007/978-3-030-87031-7_3.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6950 |
Weisser, Christoph, et al. “Using Solar Panels for Business Purposes: Evidence Based on High-Frequency Power Usage Data.” Development Engineering, vol. 6, 100016, Elsevier, 2021, doi:10.1016/j.deveng.2021.100074.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Artikel | FH-PUB-ID: 6949
Thielmann, Anton, et al. “Unsupervised Document Classification Integrating Web-Mining, One-Class SVM, and LDA Topic Modeling.” Journal of Applied Statistics, vol. 50, no. 3, Taylor & Francis, 2021, pp. 574–91, doi:10.1080/02664763.2021.1919063.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6953
Aydin, Malik, et al. “The Rhinobiome of Exacerbated Wheezers and Asthmatics: Insights From a German Pediatric Exacerbation Network.” Frontiers in Allergy, vol. 2, Frontiers Media, 2021, doi:10.3389/falgy.2021.667562.
HSBI-PUB
| DOI
2021 | Buchbeitrag | FH-PUB-ID: 6952
Thielmann, Anton, et al. “One-Class Support Vector Machine and LDA Topic Model Integration: Evidence for AI Patents.” Soft Computing for Biomedical and Related Applications, edited by Nguyen Hoang Phuong and Vladik Kreinovich, vol. Vol. 981, Springer, 2021, pp. 263–272, doi:10.1007/978-3-030-76620-7_23.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6954 |
Tillmann, Arne, et al. “AuDoLab: Automatic Document Labeling and Classification for Extremely Unbalanced Data.” Journal of Open Source Software, vol. 6, no. 66, 3719, Open Journals, 2021, doi:10.21105/joss.03719.
HSBI-PUB
| DOI
| Download (ext.)
2020 | Buch als Herausgeber | FH-PUB-ID: 6971 |
Säfken, Benjamin, et al., editors. Learning Deep: Perspectives on Deep Learning Algorithms and Artificial Intelligence. Göttingen University Press, 2020, doi:10.17875/gup2020-1338.
HSBI-PUB
| DOI
| Download (ext.)
2020 | Artikel | FH-PUB-ID: 6956 |
Kant, Gillian, et al. “TTLocVis: A Twitter Topic Location Visualization Package.” Journal of Open Source Software, vol. 5, no. 54, 2507, Open Journals, 2020, doi:10.21105/joss.02507.
HSBI-PUB
| DOI
| Download (ext.)
2014 | Diskussionspapier | FH-PUB-ID: 6972
Weisser, Christoph. Replication in the Narrow Sense of “Financial Stability, the Trilemma, and International Reserves” (Obstfeld, Shambaugh, & Taylor, 2010). Vol. 01/2014, Institut Für Statistik Und Ökonometrie, 2014.
HSBI-PUB
| Dateien verfügbar
2013 | Diskussionspapier | FH-PUB-ID: 6973
Weisser, Christoph. Hedonic Founded Cleaning of the Estimated Property Value in the Micro Survey Panel on Household Finances by Linear Stochastic Imputation. Deutsche Bundesbank, 2013.
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36 Publikationen
2026 | Artikel | FH-PUB-ID: 6961
Lukassen, Fabian, et al. “From XAI to Stories: A Factorial Study of LLM-Generated Explanation Quality.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2601.02224.
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6960
Lukassen, Fabian, et al. “LLM-Augmented Change Point Detection: A Methodological Framework for Ensemble Detection and Automated Explanation.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2601.02957.
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6959
Schlee, Michael, et al. “LabelFusion: Fusing Large Language Models With Transformer Encoders for Robust Financial News Classification.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2512.10793.
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6958
Kumar, Manish, et al. “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2604.05635 .
HSBI-PUB
| DOI
2026 | Artikel | FH-PUB-ID: 6957 |
Amorin, Alvaro Paredes, et al. “Not All News Is Equal: Topic- and Event-Conditional Sentiment From Finetuned LLMs for Aluminum Price Forecasting.” Preprint, Arxiv, 2026, doi:10.48550/arXiv.2603.09085.
HSBI-PUB
| DOI
| Download (ext.)
2026 | Artikel | FH-PUB-ID: 6924 |
Berger, Ursula, et al. “Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung.” AStA Wirtschafts- und Sozialstatistisches Archiv, Springer, 2026, doi:10.1007/s11943-026-00372-0.
HSBI-PUB
| DOI
| Download (ext.)
2025 | Artikel | FH-PUB-ID: 6962 |
Amorin, Alvaro Paredes, et al. “Fine-Tuning of Lightweight Large Language Models for Sentiment Classification on Heterogeneous Financial Textual Data.” Preprint, Arxiv, 2025, doi:10.48550/arXiv.2512.00946.
HSBI-PUB
| DOI
| Download (ext.)
2025 | Konferenzbeitrag | FH-PUB-ID: 6966 |
Semnani, Parastoo, et al. From Prediction to Proposal in Catalysis: Robust Evaluation, LRP Explanations, and Relevance-Guided Candidate Generation. Openreview, 2025.
HSBI-PUB
| Download (ext.)
2025 | Artikel | FH-PUB-ID: 6920
Reuter, Arik, et al. “Probabilistic Topic Modelling With Transformer Representations.” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 8, IEEE, 2025, pp. 14551–65, doi:10.1109/TNNLS.2025.3538262.
HSBI-PUB
| DOI
2025 | Artikel | FH-PUB-ID: 6919 |
Kant, Gillian, et al. “The Word and the Bullet: Out-Grouping and Threat Framing as Predictors of Islamic State Targeting, 2015-2020.” Terrorism and Political Violence, Taylor & Francis, 2025, doi:10.1080/09546553.2025.2561194.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 6942 |
Thielmann, Anton, et al. “Human in the Loop: How to Effectively Create Coherent Topics by Manually Labelling Only a Few Documents per Class.” Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), edited by Nicoletta Calzolari et al., Elra And Iccl, 2024, pp. 8395–405.
HSBI-PUB
| Download (ext.)
2024 | Artikel | FH-PUB-ID: 6963
Thielmann, Anton Frederik, et al. “Mambular: A Sequential Model for Tabular Deep Learning.” Preprint, Arxiv, 2024, doi:10.48550/arXiv.2408.06291.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 6964 |
Reuter, Arik, et al. “GPTopic: Dynamic and Interactive Topic Representations.” Preprint, Arxiv, 2024, doi:10.48550/arXiv.2403.03628.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Artikel | FH-PUB-ID: 6965
Stemmler, Henry, et al. “Solar Technology as a Shock-Coping Device: Evidence From Rural Tanzania.” Preprint, Ssrn, 2024, doi:10.2139/ssrn.5046518.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 6943 |
Kant, Gillian, et al. “One-Way Ticket to the Moon? An NLP-Based Insight on the Phenomenon of Small-Scale Neo-Broker Trading.” Social Network Analysis and Mining, vol. 14, 121, Springer, 2024, doi:10.1007/s13278-024-01273-2.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 6922
Thielmann, Anton Frederik, et al. “STREAM: Simplified Topic Retrieval, Exploration, and Analysis Module.” Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Volume 2: Short Papers, edited by Lun-Wei Ku et al., vol. 2, Association For Computational Linguistics, 2024, pp. 435–44, doi:10.18653/v1/2024.acl-short.41.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 6921 |
Semnani, Parastoo, et al. “A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery.” Journal of Physical Chemistry C, vol. 128, no. 50, 2024, pp. 21349–67, doi:10.1021/acs.jpcc.4c05332.
HSBI-PUB
| DOI
| Download (ext.)
2023 | Artikel | FH-PUB-ID: 6944 |
Weisser, Christoph, et al. “Pseudo-Document Simulation Method for Topic Model Evaluation on Short and Sparse Text Using Twitter Data.” Computational Statistics, vol. 38, no. 4, Springer, 2023, pp. 647–74, doi:10.1007/s00180-022-01246-z.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Artikel | FH-PUB-ID: 6967 |
Buchmüller, Andreas, et al. “Twitmo: A Twitter Data Topic Modeling and Visualization Package for R.” Preprint, Arxiv, 2022, doi:10.48550/arXiv.2207.11236.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Konferenzbeitrag | FH-PUB-ID: 6945
Tillmann, Arne, et al. “Privacy Estimation on Twitter: Modelling the Effect of Latent Topics on Privacy by Integrating XGBoost, Topic and Generalized Additive Models.” Proceedings of the 2022 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles, IoP, & SCI, edited by The Institute of Electrical and Electronics Engineers, Inc., Ieee, 2022, pp. 2325–32, doi:10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00365.
HSBI-PUB
| DOI
2022 | Artikel | FH-PUB-ID: 6946 |
Seufert, Jacqueline D., et al. “Mapping Ex-Ante Risks of COVID-19 in Indonesia Using a Bayesian Geostatistical Model on Airport Network Data.” Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 185, no. 4, Oxford University Press / Wiley, 2022, pp. 2121–55, doi:10.1111/rssa.12866.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Artikel | FH-PUB-ID: 6947 |
Kant, Gillian, et al. “Iterative Topic Model Filtering to Detect Conspiracy Theories on Twitter.” International Journal of Data Science and Analytics, Springer, 2022, doi:10.1007/s41060-022-00321-4.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Buchbeitrag | FH-PUB-ID: 6948
Kant, Gillian, et al. “Topic Model-Machine Learning Classifier Integrations on Geocoded Twitter Data.” Biomedical and Other Applications of Soft Computing, edited by Nguyen Hoang Phuong and Vladik Kreinovich, Springer, 2022, doi:10.1007/978-3-031-08580-2_11.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6968 |
Luber, Mattias, et al. “Community Detection via Hashtag-Graphs for Semi-Supervised NMF Topic Models.” Preprint, Arxiv, 2021, doi:10.48550/arXiv.2111.10401.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Buch als Herausgeber | FH-PUB-ID: 6970 |
Kruse , René-Marcel, et al., editors. Learning Deep Textwork: Perspectives on Natural Language Processing and Artificial Intelligence. Göttingen University Press, 2021, doi:10.17875/gup2021-1608.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Artikel | FH-PUB-ID: 6955 |
Thormann, Marah-Lisanne, et al. “Stock Price Predictions With LSTM Neural Networks and Twitter Sentiment.” Statistics, Optimization & Information Computing, vol. 9, no. 2, International Academic Press, 2021, pp. 268–87, doi:10.19139/soic-2310-5070-1202.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Konferenzbeitrag | FH-PUB-ID: 6951
Luber, Mattias, et al. “Identifying Topical Shifts in Twitter Streams: An Integration of Non-Negative Matrix Factorisation, Sentiment Analysis, and Structural Break Models for Large-Scale Data.” Disinformation in Open Online Media. MISDOOM 2021, edited by Jonathan Bright et al., Springer, 2021, pp. 33–49, doi:10.1007/978-3-030-87031-7_3.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6950 |
Weisser, Christoph, et al. “Using Solar Panels for Business Purposes: Evidence Based on High-Frequency Power Usage Data.” Development Engineering, vol. 6, 100016, Elsevier, 2021, doi:10.1016/j.deveng.2021.100074.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Artikel | FH-PUB-ID: 6949
Thielmann, Anton, et al. “Unsupervised Document Classification Integrating Web-Mining, One-Class SVM, and LDA Topic Modeling.” Journal of Applied Statistics, vol. 50, no. 3, Taylor & Francis, 2021, pp. 574–91, doi:10.1080/02664763.2021.1919063.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6953
Aydin, Malik, et al. “The Rhinobiome of Exacerbated Wheezers and Asthmatics: Insights From a German Pediatric Exacerbation Network.” Frontiers in Allergy, vol. 2, Frontiers Media, 2021, doi:10.3389/falgy.2021.667562.
HSBI-PUB
| DOI
2021 | Buchbeitrag | FH-PUB-ID: 6952
Thielmann, Anton, et al. “One-Class Support Vector Machine and LDA Topic Model Integration: Evidence for AI Patents.” Soft Computing for Biomedical and Related Applications, edited by Nguyen Hoang Phuong and Vladik Kreinovich, vol. Vol. 981, Springer, 2021, pp. 263–272, doi:10.1007/978-3-030-76620-7_23.
HSBI-PUB
| DOI
2021 | Artikel | FH-PUB-ID: 6954 |
Tillmann, Arne, et al. “AuDoLab: Automatic Document Labeling and Classification for Extremely Unbalanced Data.” Journal of Open Source Software, vol. 6, no. 66, 3719, Open Journals, 2021, doi:10.21105/joss.03719.
HSBI-PUB
| DOI
| Download (ext.)
2020 | Buch als Herausgeber | FH-PUB-ID: 6971 |
Säfken, Benjamin, et al., editors. Learning Deep: Perspectives on Deep Learning Algorithms and Artificial Intelligence. Göttingen University Press, 2020, doi:10.17875/gup2020-1338.
HSBI-PUB
| DOI
| Download (ext.)
2020 | Artikel | FH-PUB-ID: 6956 |
Kant, Gillian, et al. “TTLocVis: A Twitter Topic Location Visualization Package.” Journal of Open Source Software, vol. 5, no. 54, 2507, Open Journals, 2020, doi:10.21105/joss.02507.
HSBI-PUB
| DOI
| Download (ext.)
2014 | Diskussionspapier | FH-PUB-ID: 6972
Weisser, Christoph. Replication in the Narrow Sense of “Financial Stability, the Trilemma, and International Reserves” (Obstfeld, Shambaugh, & Taylor, 2010). Vol. 01/2014, Institut Für Statistik Und Ökonometrie, 2014.
HSBI-PUB
| Dateien verfügbar
2013 | Diskussionspapier | FH-PUB-ID: 6973
Weisser, Christoph. Hedonic Founded Cleaning of the Estimated Property Value in the Micro Survey Panel on Household Finances by Linear Stochastic Imputation. Deutsche Bundesbank, 2013.
HSBI-PUB