Items where Subject is "Institute of Data Science > Data Analysis and Intelligence"

Institutes and Facilities (127801)
- Institute of Data Science (399)
  - Data Analysis and Intelligence (35)

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Number of items at this level: 35.

B

Bodesheim, Paul and Blunk, Jan and Körschens, Matthias and Brust, Clemens-Alexander and Käding, Christoph and Denzler, Joachim (2022) Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research—Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes. Mammalian Biology. Springer. doi: 10.1007/s42991-022-00224-8. ISSN 1616-5047.

Bouhlal, Badr-Eddine and Gruner, Bernd and Sonnekalb, Tim and Brust, Clemens-Alexander (2022) Machine Learning Applications in Secure Software Engineering. WissensAustauschWorkshop Machine Learning, 7.9. Nov. 2022, Jena, Deutschland.

Boyé, Pascal (2022) Betrachtung der Gradientenbestimmung für den Adam Algorithmus. Bachelor's, Technische Universität Ilmenau. Volltext nicht frei.

Brust, Clemens-Alexander and Barz, Björn and Denzler, Joachim (2022) Self-Supervised Learning from Semantically Imprecise Data. In: 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2022, 5, pp. 27-35. SCITEPRESS. Computer Vision Theory and Applications (VISAPP), 6.-8. Feb. 2022, Online. doi: 10.5220/0010766700003124. ISBN 978-989-758-555-5. ISSN 2184-4321.

D

Dietenberger, Steffen and Müller, Marlin and Adam, Markus and Bachmann, Felix and Metz, Friederike and Nestler, Maximilian and Hese, Sören and Thiel, Christian (2023) Digital forest inventory based on UAV imagery. European Geosciences Union General Assembly 2023, 23.-28.04.2023, Wien, Österreich. Volltext nicht online.

G

Gerhardus, Andreas (2022) Learning cause-and-effect relationships from time series data. 1st Causal Methods in Environmental Science Workshop, Hybrid (Cambridge, UK, und online). Volltext nicht frei.

Gerhardus, Andreas (2022) Kausale Inferenz: Datengetriebene Analyse von Ursache-Wirkungs-Zusammenhängen. Herbsttagung 2022 der German Data Science Society e.V., Bonn, Deutschland. Volltext nicht frei.

Gerhardus, Andreas (2022) Reliable causal discovery in time series. Workshop on Artificial Intelligence, Causality and Personalised Medicine (AICPM 2022), Hybrid (Hannover, Deutschland, und online).

Gerhardus, Andreas and Runge, Jakob (2022) Causal Discovery in Ensembles of Climate Time Series. EGU General Assembly 2022, Hybrid (Wien, Östereich, und virtuell). Volltext nicht online.

Gerhardus, Andreas and Runge, Jakob (2022) Numerical study of constraint-based time series causal discovery algorithms on synthetic data with heavy-tailed noise distributions. Workshop on Combining Causal Inference and Extreme Value Theory in the Study of Climate Extremes and their Causes, Hybrid (Kelowna, Kanada, und virtuell). Volltext nicht online.

K

Koebsch, Frankziska and Mund, Martina and Klosterhalfen, Anne and Dietenberger, Steffen and Donfack, Laura and Heidenreich, Marius and Markwitz, Christian and Montero, David and Thiel, Christian and Tiedemann, Frank and Knohl, Alexander (2023) Stress response and transformation processes initiated by the summer drought 2018 - a multi-scale study from the Hainich forest. European Geosciences Union General Assembly 2023, 23. - 28.04.2023, Wien, Österreich. doi: 10.5194/egusphere-egu23-14520. Volltext nicht online.

Krich, Christopher and Mahecha, Miguel and Migliavacca, Mirco and De Kauwe, Martin G and Griebel, Anne and Runge, Jakob and Miralles, Diego G (2022) Decoupling between ecosystem photosynthesis and transpiration: a last resort against overheating. Environmental Research Letters. Institute of Physics (IOP) Publishing. doi: 10.1088/1748-9326/ac583e. ISSN 1748-9326.

N

Niebling, Julia (2022) A multiobjective view on creating counterfactual explanations for explaining uncertainty in machine learning. [Other]

Nussbaum, Frank / FN and Gawlikowski, Jakob / JG and Niebling, Julia (2022) Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks. Conference on Neural Information Processing Systems (NeuRIPS), New Orleans. Volltext nicht frei.

R

Reimers, Christian and Bodesheim, Paul and Runge, Jakob and Denzler, Joachim (2022) Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. In: Pattern Recognition, 43rd DAGM German Conference, DAGM GCPR 2021, 13024. Springer, Cham. 43rd DAGM German Conference for Pattern Recognition, 28. Sept. - 01. Okt. 2021, Bonn, Deutschland. doi: 10.1007/978-3-030-92659-5_4. Volltext nicht online.

Rewicki, Ferdinand and Denzler, Joachim and Niebling, Julia (2023) Is It Worth It? Comparing Six Deep and Classical Methods for Unsupervised Anomaly Detection in Time Series. Applied Sciences. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/app13031778. ISSN 2076-3417.

Rewicki, Ferdinand and Gawlikowski, Jakob (2022) ESTIMATING UNCERTAINTY OF DEEP LEARNING MULTI-LABEL CLASSIFICATIONS USING LAPLACE APPROXIMATION. In: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, pp. 1560-1563. IEEE. IGARSS 2022 - IEEE International Geoscience and Remote Sensing Symposium, 17.-22. Juli 2022, Kuala Lumpur, Malaysia. doi: 10.1109/IGARSS46834.2022.9884167. ISBN 978-1-6654-2792-0. ISSN 2153-7003. Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery with perspectives in Earth sciences. Seminar, Nairobi, Kenia. Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery with perspectives in Earth sciences. Columbia University Seminar, New York, USA. Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery with perspectives in Earth sciences. Helmholtz Center Munich Seminar Series, Munich, Deutschland (virtuell). Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery with perspectives in Earth sciences. Inverse Network Dynamics - Network structure and function from nonlinear dynamics and time series data, Dresden, Deutschland. Volltext nicht online.

Runge, Jakob (2022) Explainable AI in climate science and its limitations. Lorentz Center Workshop on subseasonal prediction, Leiden, Niederlande. Volltext nicht online.

Runge, Jakob (2022) Combining Causal Inference and Extreme Value Theory in the Study of Climate Extremes and their Causes. BANFF Workshop in Extremes and causality, Banff, Kanada (Virtuell). Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery with perspectives in Earth sciences. Aspen workshop Exploring the frontiers in Earth system modeling with machine learning and big data, Aspen, USA (virtuell). Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery. causality conference at Madrid, Madrid, Spanien. Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery. Simulation-based Science Community Series, Amsterdam, Niederlande. Volltext nicht online.

Runge, Jakob (2022) Causal Inference and discovery with perspectives in Earth sciences. CMU/STAMPS webinar, Pittsburgh, USA (virtuell). Volltext nicht online.

Runge, Jakob (2021) Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables. In: 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Curran Associates, Inc.. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 06.-14. Dez. 2021, Virtuell. ISBN 978-171384539-3. ISSN 1049-5258.

Runge, Jakob and Ebert-Uphoff, Imme (2022) Causal inference for Earth system sciences. AI4Good, Genf, Schweiz (Virtuell). Volltext nicht online.

S

Schulte-Kroll, Anne (2022) Unsupervised Learning of Reusable Text Sequence Representations for IT-Infrastructure Health Monitoring using Anomaly Detection. Master's, FSU Jena. Volltext nicht frei.

Sonnekalb, Tim and Gruner, Bernd and Brust, Clemens-Alexander and Mäder, Patrick (2022) Generalizability of Code Clone Detection on CodeBERT. In: Automated Software Engieering. ACM. ASE 2022, 10. - 14. Okt. 2022, Michigan, USA.

Sudheesh, Saranya Ganesh and Beucler, Tom Georges and Tam, Frederick Iat-Hin and Gerhardus, Andreas and Runge, Jakob (2023) Causal Discovery to Improve Machine Learning-Based Tropical Cyclone Intensity Predictions. 103rd AMS annual meeting, Denver, CO, USA und Online. Volltext nicht online.

U

Ulman, Hannah and Gütter, Jonas Aaron and Niebling, Julia (2023) Uncertainty is not sufficient for identifying noisy labels in training data for binary segmentation of building footprints. Frontiers in Remote Sensing (3), p. 1100012. Frontiers Media S.A.. doi: 10.3389/frsen.2022.1100012. ISSN 2673-6187.

V

Veselova, Inna (2022) Evaluation von verteilten Algorithmen zur Diabeteserkennung unter Beachtung des Datenschutzes. Bachelor's. Volltext nicht frei.

W

Wen, Jiaming and Runge, Jakob and Gerhardus, Andreas and Sun, Ying (2022) Understanding and Predicting the Interannual Variability (IAV) of the Global Terrestrial Carbon Cycle. AGU Fall Meeting, Chicago, IL, USA und Online. (Unpublished) Volltext nicht online.

This list was generated on Fri May 26 21:04:44 2023 CEST.