Profile Page Prof. Dr. Damian Borth

Latest Additions (all)

1. Schreyer, Marco; Hemati, Hamed; Borth, Damian & Vasarhelyi, Miklos A.: Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing. 2022. - Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022). - New Orleans, LA, USA.
2. Schreyer, Marco; Sattarov, Timur & Borth, Damian: Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. 2022. - 3rd ACM International Conference on Artificial Intelligence in Finance (ICAIF). - New York City, USA.
3. Schürholt, Konstantin; Knyazev, Boris; Giro-i-Nieto, Xavier & Borth, Damian: Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. 2022. - Conference on Neural Information Processing Systems. - New Orleans.
4. Schürholt, Konstantin; Taskiran, Diyar; Knyazev, Boris; Giro-i-Nieto, Xavier & Borth, Damian: Model Zoos: A Dataset of Diverse Populations of Neural Network Models. 2022. - 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks..
5. Hanna, Joëlle; Mommert, Michael & Borth, Damian: Estimation of Power Generation and CO2 Emissions Using Satellite Imagery. 2022. - AI4EO Symposium. - Munich.
6. Scheibenreif, Linus Mathias; Hanna, Joëlle; Mommert, Michael & Borth, Damian: Multi-modal Self-supervised Learning for Earth Observation. [Conference or Workshop Item]
7. Mommert, Michael; Blattner, Moritz; Eicher, Leonardo & Borth, Damian: Quantifying Traffic with Deep Learning from Earth Observation Data. [Conference or Workshop Item]
8. Eicher, Leonardo; Mommert, Michael & Borth, Damian: Traffic Noise Estimation from Satellite Imagery with Deep Learning. 2022. - IEEE Geoscience and Remote Sensing Symposium 2022. - Kuala Lumpur, Malaysia.
9. Hanna, Joëlle; Scheibenreif, Linus Mathias; Mommert, Michael & Borth, Damian: A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020. 2022. - IEEE Geoscience and Remote Sensing Symposium 2022. - Kuala Lumpur, Malaysia.
10. Scheibenreif, Linus Mathias; Hanna, Joëlle; Mommert, Michael & Borth, Damian: Self-supervised Vision Transformers for Land-cover Segmentation and Classification. 2022.

Most Viewed Items

	Item title	Views
1	Künstliche Intelligenz in der Wirtschaftsprüfung - Identifikation ungewöhnlicher Buchungen in der Finanzbuchhaltung	2697
2	Management von Künstlicher Intelligenz in Unternehmen	2186
3	Open Grid - Open Mind	2055
4	Künstliche Intelligenz in der Prüfungspraxis - Eine Bestandsaufnahme aktueller Einsatzmöglichkeiten und Herausforderungen	1849
5	Adversarial Learning of Deepfakes in Accounting	1756
6	Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks	1664
7	Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks	1594
8	EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification	1511
9	Learning Sampling in Financial Statement Audits using Vector Quantised Variational Autoencoder Neural Networks	1468
10	Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Neural Networks	1434