Suchergebnisse - "11555 Department of Mathematical Modeling and Machine Learning"

Lossy Neural Compression for Geospatial Analytics: A review

Autoren: Gomes, Carlos Wittmann, Isabelle Robert, Damien et al.

Weitere Verfasser: Gomes, Carlos Wittmann, Isabelle Robert, Damien et al.

Quelle: IEEE Geoscience and Remote Sensing Magazine. 13:97-135

Schlagwörter: Signal Processing (eess.SP), FOS: Computer and information sciences, 11555 Department of Mathematical Modeling and Machine Learning, 3105 Instrumentation, 2208 Electrical and Electronic Engineering, Computer Vision and Pattern Recognition (cs.CV), 1900 General Earth and Planetary Sciences, Earth System Models, FOS: Physical sciences, Machine Learning (cs.LG), Geophysics (physics.geo-ph), Machine Learning, 510 Mathematics, Geophysics, Artificial Intelligence (cs.AI), Neural Compression, Artificial Intelligence, Signal Processing, FOS: Electrical engineering, electronic engineering, information engineering, Earth Observation, Geospatial Analytics, 1700 General Computer Science, Computer Vision and Pattern Recognition

Dateibeschreibung: 2025Wegner_Lossy.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2503.01505
https://elib.dlr.de/212973/
https://doi.org/10.1109/mgrs.2025.3546527
https://www.zora.uzh.ch/id/eprint/277902/
https://doi.org/10.5167/uzh-277902

Quantifying the Spread of Online Incivility in Brazilian Politics

Autoren: Zhang, Yuan Amsler, Michael Herrero, Laia Castro et al.

Weitere Verfasser: Zhang, Yuan Amsler, Michael Herrero, Laia Castro et al.

Quelle: Proceedings of the International AAAI Conference on Web and Social Media. 19:2241-2259

Schlagwörter: Social and Information Networks (cs.SI), FOS: Computer and information sciences, 510 Mathematics, 11555 Department of Mathematical Modeling and Machine Learning, Computer Science - Social and Information Networks

Dateibeschreibung: Bovet2025_Quantifying.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2504.08960
https://www.zora.uzh.ch/id/eprint/279482/
https://doi.org/10.5167/uzh-279482

Deep learning meets tree phenology modelling: PhenoFormer versus process‐based models

Autoren: Garnot, Vivien Sainte Fare Spafford, Lynsay Lever, Jelle et al.

Weitere Verfasser: Garnot, Vivien Sainte Fare Spafford, Lynsay Lever, Jelle et al.

Quelle: Methods in Ecology and Evolution, Vol 16, Iss 7, Pp 1489-1506 (2025)

Schlagwörter: Ecology, Evolution, 11555 Department of Mathematical Modeling and Machine Learning, deep learning, process‐based models, climate phenology modelling, 510 Mathematics, 1105 Ecology, Evolution, Behavior and Systematics, 2302 Ecological Modeling, processbased models, Climate change phenology projection, QH359-425, QH540-549.5, climate change phenology projection

Dateibeschreibung: Wegner2025_DeepLearning.pdf - application/pdf

Zugangs-URL: https://doaj.org/article/299f5c9af0bb4c82ac25594e1c3467c3

Uncertainties in Field Spectroscopy: Operator and Setup Induced Effects on Spectral Radiance Measurements

Autoren: Carmen Meiller Andreas Hueni Reinhard Furrer et al.

Weitere Verfasser: Carmen Meiller Andreas Hueni Reinhard Furrer et al.

Quelle: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 584-606 (2025)

Schlagwörter: radiance, reflectance factor, QC801-809, 11555 Department of Mathematical Modeling and Machine Learning, uncertainty estimation, Geophysics. Cosmic physics, 1903 Computers in Earth Sciences, 04 agricultural and veterinary sciences, 01 natural sciences, Ocean engineering, 10123 Institute of Mathematics, 510 Mathematics, 10122 Institute of Geography, CAL/VAL, field spectroscopy (FS), Ground Truth, 1902 Atmospheric Science, 0401 agriculture, forestry, and fisheries, 910 Geography & travel, TC1501-1800, 0105 earth and related environmental sciences

Dateibeschreibung: 2024_Meiller_Uncertainties_in_Field_Spectroscopy_Operator_and_Setup_Induced_Effects_on_Spectral_Radiance_Measurements.pdf - application/pdf

Zugangs-URL: https://doaj.org/article/f2578d1ba66c45aba0f768542eeed9ba

Population connectivity shapes the distribution and complexity of chimpanzee cumulative culture

Autoren: Gunasekaram, Cassandra Battiston, Federico Sadekar, Onkar et al.

Weitere Verfasser: Gunasekaram, Cassandra Battiston, Federico Sadekar, Onkar et al.

Quelle: Digital.CSIC. Repositorio Institucional del CSIC
Consejo Superior de Investigaciones Científicas (CSIC)

Schlagwörter: Genetic Markers, 0301 basic medicine, 0303 health sciences, Pan troglodytes, 300 Social sciences, sociology & anthropology, 11555 Department of Mathematical Modeling and Machine Learning, 10207 Department of Evolutionary Anthropology, 2204 Biomedical Engineering, Biological Evolution, 10123 Institute of Mathematics, 03 medical and health sciences, 510 Mathematics, 1300 General Biochemistry, Genetics and Molecular Biology, Cultural Evolution, 1706 Computer Science Applications, Animals, Animal Migration, Social Behavior

Dateibeschreibung: application/pdf; science.adk3381_1.pdf - application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39571020
https://api.elsevier.com/content/abstract/scopus_id/85210462844
http://hdl.handle.net/10261/383298
https://research.ceu.edu/en/publications/e5c5bad6-49af-4bc4-ac19-9fc38dbdf6c5
https://doi.org/10.1126/science.adk3381

Point2CAD: Reverse Engineering CAD Models from 3D Point Clouds

Autoren: Liu, Yujia Obukhov, Anton Wegner, Jan Dirk et al.

Weitere Verfasser: Liu, Yujia Obukhov, Anton Wegner, Jan Dirk et al.

Quelle: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). :3763-3772

Schlagwörter: 1712 Software, FOS: Computer and information sciences, 510 Mathematics, 1707 Computer Vision and Pattern Recognition, 11476 Digital Society Initiative, 11555 Department of Mathematical Modeling and Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition

Dateibeschreibung: 2024Wegner_Point2CAD_ReverseEngineerig.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2312.04962
https://www.zora.uzh.ch/id/eprint/266330/
https://doi.org/10.5167/uzh-266330

Point2Building: Reconstructing buildings from airborne LiDAR point clouds

Autoren: Liu, Yujia Obukhov, Anton Wegner, Jan Dirk et al.

Weitere Verfasser: Liu, Yujia Obukhov, Anton Wegner, Jan Dirk et al.

Quelle: ISPRS Journal of Photogrammetry and Remote Sensing. 215:351-368

Schlagwörter: FOS: Computer and information sciences, 11476 Digital Society Initiative, 11555 Department of Mathematical Modeling and Machine Learning, Computer Vision and Pattern Recognition (cs.CV), 1903 Computers in Earth Sciences, Computer Science - Computer Vision and Pattern Recognition, Deep learning, 04 agricultural and veterinary sciences, 02 engineering and technology, 3107 Atomic and Molecular Physics, and Optics, Building reconstruction, Airborne LiDAR point clouds, 510 Mathematics, Transformers, 11. Sustainability, 1706 Computer Science Applications, 0202 electrical engineering, electronic engineering, information engineering, 0401 agriculture, forestry, and fisheries, 2201 Engineering (miscellaneous), Autoregressive generative models

Dateibeschreibung: ZORA_1_s2_0_S092427162400279X_main.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2403.02136

Digital innovations for monitoring sustainability in food systems

Autoren: Meemken, Eva-Marie Becker-Reshef, Inbal Klerkx, Laurens et al.

Weitere Verfasser: Meemken, Eva-Marie Becker-Reshef, Inbal Klerkx, Laurens et al.

Quelle: Nature Food. 5:656-660

Schlagwörter: Big Data, 0301 basic medicine, 2. Zero hunger, Digital Technology, 0303 health sciences, 11476 Digital Society Initiative, 11555 Department of Mathematical Modeling and Machine Learning, Sustainable Development, Food Supply, 12. Responsible consumption, Machine Learning, 03 medical and health sciences, 510 Mathematics, Blockchain, 13. Climate action, Remote Sensing Technology, Life Science, Humans, 1102 Agronomy and Crop Science, Smartphone, 1103 Animal Science and Zoology, 1106 Food Science

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39147913
https://research.wur.nl/en/publications/digital-innovations-for-monitoring-sustainability-in-food-systems
https://doi.org/10.1038/s43016-024-01018-6
https://www.zora.uzh.ch/id/eprint/266320/
https://doi.org/10.5167/uzh-266320

Compatibility of space‐time kernels with full, dynamical, or compact support

Autoren: Faouzi, Tarik Furrer, Reinhard Porcu, Emilio et al.

Weitere Verfasser: Faouzi, Tarik Furrer, Reinhard Porcu, Emilio et al.

Quelle: Mathematical Methods in the Applied Sciences. 48:1216-1225

Schlagwörter: rn covariance, domain asymptotics, microergodic parameterprediction, 11555 Department of Mathematical Modeling and Machine Learning, Author Keywords: fixed, space, 01 natural sciences, 510 Mathematics, Mat & eacute, time generalized Wendland family Keywords: PlusCOVARIANCE FUNCTIONS MSC classification: 60G60, 42A82, 2200 General Engineering, maximum likelihood, 62M40, 0101 mathematics, 2600 General Mathematics

Dateibeschreibung: Furrer2024_compatibilityOfSpcae_TimeKernels.pdf - application/pdf

Graph spring neural ODEs for link sign prediction

Autoren: Rehmann, Andrin Bovet, Alexandre University of Zurich

Weitere Verfasser: Rehmann, Andrin Bovet, Alexandre University of Zurich

Quelle: Machine Learning. 114

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Node representation learning, I.2.4, I.2.6, 11555 Department of Mathematical Modeling and Machine Learning, 1702 Artificial Intelligence, Sign prediction, Machine Learning (cs.LG), 1712 Software, Graph machine learning, Computer Science - Computers and Society, 510 Mathematics, Computers and Society (cs.CY), Neural graph ordinary differential equations, Signed graphs

Dateibeschreibung: ZORA_s10994_025_06794_1.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2412.12916
https://www.zora.uzh.ch/id/eprint/279478/
https://doi.org/10.5167/uzh-279478

Towards ROXAS AI: automatic multi-species ring boundaries segmentation as regression in anatomical images

Autoren: Marc Katzenmaier Vivien Sainte Fare Garnot Jan Dirk Wegner et al.

Weitere Verfasser: Marc Katzenmaier Vivien Sainte Fare Garnot Jan Dirk Wegner et al.

Quelle: Front Plant Sci
Frontiers in Plant Science, Vol 16 (2025)

Schlagwörter: neural network, 11555 Department of Mathematical Modeling and Machine Learning, Plant culture, deep learning, Plant Science, tree ring, SB1-1110, shrubs, 510 Mathematics, ROXAS, quantitative wood anatomy, 1110 Plant Science, Keywords: tree ring, image segmentation

Dateibeschreibung: 2025Wegner_towardsROXAS_AI.pdf - application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40395279
https://doaj.org/article/d4076e9143624265a14cdae4e25dfe91
https://www.zora.uzh.ch/id/eprint/277900/
https://doi.org/10.5167/uzh-277900

Uncertainty Voting Ensemble for Imbalanced Deep Regression

Autoren: Jiang, Yuchang Garnot, Vivien Sainte Fare Schindler, Konrad et al.

Weitere Verfasser: Jiang, Yuchang Garnot, Vivien Sainte Fare Schindler, Konrad et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783031851803

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, 510 Mathematics, 11555 Department of Mathematical Modeling and Machine Learning, 1700 General Computer Science, 2614 Theoretical Computer Science, Machine Learning (cs.LG)

Dateibeschreibung: 2025Wegner_Uncertainty.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2305.15178
https://www.zora.uzh.ch/id/eprint/279485/
https://doi.org/10.5167/uzh-279485

Recognition of Unseen Bird Species by Learning from Field Guides

Autoren: Rodríguez, Andrés C D'Aronco, Stefano Daudt, Rodrigo Caye et al.

Weitere Verfasser: Rodríguez, Andrés C D'Aronco, Stefano Daudt, Rodrigo Caye et al.

Quelle: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). :1731-1740

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, 1707 Computer Vision and Pattern Recognition, 11555 Department of Mathematical Modeling and Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 1702 Artificial Intelligence, 02 engineering and technology, Machine Learning (cs.LG), 03 medical and health sciences, 510 Mathematics, 0302 clinical medicine, 1706 Computer Science Applications, 0202 electrical engineering, electronic engineering, information engineering

Dateibeschreibung: Wegner2024_IEEE_RecognitionofUnseenBird.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2206.01466

Sat-SINR: High-Resolution Species Distribution Models Through Satellite Imagery

Autoren: Dollinger, Johannes Brun, Philipp Sainte Fare Garnot, Vivien et al.

Weitere Verfasser: Dollinger, Johannes Brun, Philipp Sainte Fare Garnot, Vivien et al.

Quelle: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-2-2024, Pp 41-48 (2024)

Schlagwörter: Technology, 11476 Digital Society Initiative, 11555 Department of Mathematical Modeling and Machine Learning, 3105 Instrumentation, 1901 Earth and Planetary Sciences (miscellaneous), deep learning, 2301 Environmental Science (miscellaneous), species distribution modeling, 15. Life on land, Engineering (General). Civil engineering (General), TA1501-1820, 510 Mathematics, multi, modal fusion, Applied optics. Photonics, sentinel, TA1-2040

Dateibeschreibung: application/pdf; ZORA_isprs_annals_X_2_2024_41_2024.pdf - application/pdf

Zugangs-URL: https://isprs-annals.copernicus.org/articles/X-2-2024/41/2024/
https://doaj.org/article/d8034b52f60b4fbab7cdc7b017f79ee1

An open-source tool for mapping war destruction at scale in Ukraine using Sentinel-1 time series

Autoren: Dietrich, Olivier Peters, Torben Sainte Fare Garnot, Vivien et al.

Weitere Verfasser: Dietrich, Olivier Peters, Torben Sainte Fare Garnot, Vivien et al.

Quelle: Communications Earth & Environment, Vol 6, Iss 1, Pp 1-10 (2025)

Schlagwörter: 2300 General Environmental Science, Environmental sciences, FOS: Computer and information sciences, QE1-996.5, 11555 Department of Mathematical Modeling and Machine Learning, Computer Vision and Pattern Recognition (cs.CV), 320 Political science, 1900 General Earth and Planetary Sciences, Computer Science - Computer Vision and Pattern Recognition, 10113 Institute of Political Science, Geology, GE1-350

Dateibeschreibung: ZORA_s43247_025_02183_7.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2406.02506
https://doaj.org/article/67000a415fbb46edae976bccea2ae672

Lost in translation: using global fact-checks to measure multilingual misinformation prevalence, spread, and evolution

Autoren: Quelle, Dorian Cheng, Calvin Yixiang Bovet, Alexandre et al.

Weitere Verfasser: Quelle, Dorian Cheng, Calvin Yixiang Bovet, Alexandre et al.

Quelle: EPJ Data Science, Vol 14, Iss 1, Pp 1-24 (2025)

Schlagwörter: 11555 Department of Mathematical Modeling and Machine Learning, Fact, Computer applications to medicine. Medical informatics, R858-859.7, Multilingual NLP, Keywords: Misinformation, checking, Fact-checking, Social media, 510 Mathematics, 1706 Computer Science Applications, Misinformation, Information diffusion, 2605 Computational Mathematics, 2611 Modeling and Simulation

Dateibeschreibung: ZORA_s13688_025_00520_6.pdf - application/pdf

Zugangs-URL: https://doaj.org/article/c6ed4cbab3c5429589c0f31e8426fa7c
https://ora.ox.ac.uk/objects/uuid:be87659e-239c-4504-a23d-965105ecc795
https://doi.org/10.1140/epjds/s13688-025-00520-6
https://www.zora.uzh.ch/id/eprint/277895/
https://doi.org/10.5167/uzh-277895

Longitudinal modularity, a modularity for link streams

Autoren: Brabant, Victor Asgari, Yasaman Borgnat, Pierre et al.

Weitere Verfasser: Brabant, Victor Asgari, Yasaman Borgnat, Pierre et al.

Quelle: EPJ Data Science, Vol 14, Iss 1, Pp 1-20 (2025)

Schlagwörter: Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Machine Learning, 11555 Department of Mathematical Modeling and Machine Learning, [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI], Computer applications to medicine. Medical informatics, Community structures, R858-859.7, Modularity, Temporal networks, Computer Science - Social and Information Networks, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], Computer Science - Information Retrieval, Machine Learning (cs.LG), 510 Mathematics, Link streams, 1706 Computer Science Applications, [INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR], 2605 Computational Mathematics, [PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an], Information Retrieval (cs.IR), 2611 Modeling and Simulation

Dateibeschreibung: application/pdf; ZORA_s13688_025_00529_x.pdf - application/pdf

Zugangs-URL: http://arxiv.org/abs/2408.16877
https://doaj.org/article/23c98128c32c4b66a35a9a58aa3fa3fa
https://hal.science/hal-04731945v2/document
https://hal.science/hal-04731945v2
https://doi.org/10.1140/epjds/s13688-025-00529-x
https://www.zora.uzh.ch/id/eprint/277896/
https://doi.org/10.5167/uzh-277896

Anatomical, functional, and blood-born predictors of severity of brachycephalic obstructive airway syndrome severity in French Bulldogs

Autoren: Claudia Schmid Aline R. Steiner Léonie Spielhofer et al.

Weitere Verfasser: Claudia Schmid Aline R. Steiner Léonie Spielhofer et al.

Quelle: Front Vet Sci
Frontiers in Veterinary Science, Vol 11 (2025)

Schlagwörter: brachycephaly, 10253 Department of Small Animals, severity grading, 11555 Department of Mathematical Modeling and Machine Learning, 3400 General Veterinary, Veterinary medicine, trotting test, 10081 Institute of Veterinary Physiology, 10187 Department of Farm Animals, SF600-1100, 11404 Department of Clinical Diagnostics and Services, 570 Life sciences, biology, whole body plethysmography, Veterinary Science, 10599 Chair in Veterinary Epidemiology, 11434 Center for Clinical Studies, brachycephalic obstructive airway syndrome, anatomical conformation

Dateibeschreibung: fvets_11_1486440.pdf - application/pdf

Zugangs-URL: https://doaj.org/article/b79cc11e7c284bdab5b31ca8e2b9ce45
https://www.zora.uzh.ch/id/eprint/270208/
https://doi.org/10.5167/uzh-270208

Constraints on the photon polarisation in b → sγ transitions using ${B}_s^0$ → ϕe+e− decays

Autoren: Aaij, R Abdelmotteleb, A S W Abellan Beteta, C et al.

Weitere Verfasser: Aaij, R Abdelmotteleb, A S W Abellan Beteta, C et al.

Schlagwörter: 510 Mathematics, Hadron Scattering, 11555 Department of Mathematical Modeling and Machine Learning, Keywords: B Physics, Hadron, Flavour Changing Neutral Currents, Rare Decay, 10192 Physics Institute, 3106 Nuclear and High Energy Physics

Dateibeschreibung: ZORA_JHEP03_2025_047.pdf - application/pdf

Strategies for Interdisciplinary Human Gene Editing Research: Insights from a Swiss Project

Autoren: Kandlbinder, Agnes Peter-Spiess, Marie-Hélène Leeners, Brigitte et al.

Weitere Verfasser: Kandlbinder, Agnes Peter-Spiess, Marie-Hélène Leeners, Brigitte et al.

Quelle: The CRISPR journal.

Schlagwörter: 10892 Constitutional, Administrative and International Law, human gene editing, 11555 Department of Mathematical Modeling and Machine Learning, 10050 Institute of Pharmacology and Toxicology, 10175 Clinic for Reproductive Endocrinology, 10246 Department of Social Anthropology and Cultural Studies, ethics, collaboration, CRISPR clinical application, 170 Ethics, responsible research, interdisciplinarity, 1311 Genetics, basic research, 1305 Biotechnology, 10001 Center for Ethics

Dateibeschreibung: CRISPR_J_Manuscript_ZORA.pdf - application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40173337