| Deep neural networks and tabular data: A survey V Borisov, T Leemann, K Seßler, J Haug, M Pawelczyk, G Kasneci IEEE transactions on neural networks and learning systems, 2022 | 898 | 2022 |
| Language models are realistic tabular data generators V Borisov, K Seßler, T Leemann, M Pawelczyk, G Kasneci International Conference on Learning Representations (ICLR), 2023 | 212 | 2023 |
| A consistent and efficient evaluation strategy for attribution methods Y Rong, T Leemann, V Borisov, G Kasneci, E Kasneci International Conference on Machine Learning (ICML), 2022 | 113 | 2022 |
| CancelOut: A Layer for Feature Selection in Deep Neural Networks V Borisov, J Haug, G Kasneci Artificial Neural Networks and Machine Learning–ICANN 2019: Deep Learning …, 2019 | 63 | 2019 |
| Robust cognitive load detection from wrist-band sensors V Borisov, E Kasneci, G Kasneci Computers in Human Behavior Reports 4, 100116, 2021 | 31 | 2021 |
| Lithography hotspots detection using deep learning V Borisov, J Scheible 2018 15th international conference on synthesis, modeling, analysis and …, 2018 | 27 | 2018 |
| DeepTLF: Robust Deep Neural Networks for Heterogeneous Tabular Data V Borisov, K Broelemann, E Kasneci, G Kasneci International Journal of Data Science and Analytics, 2022 | 26 | 2022 |
| Lessons learned from the 1st Ariel Machine Learning Challenge: Correcting transiting exoplanet light curves for stellar spots N Nikolaou, IP Waldmann, A Tsiaras, M Morvan, B Edwards, KH Yip, ... RAS Techniques and Instruments 2 (1), 695-709, 2023 | 14 | 2023 |
| Evaluating feature attribution: An information-theoretic perspective Y Rong, T Leemann, V Borisov, G Kasneci, E Kasneci CoRR, 2022 | 9 | 2022 |
| Research on data augmentation for lithography hotspot detection using deep learning V Borisov, J Scheible 34th European Mask and Lithography Conference 10775, 204-209, 2018 | 8 | 2018 |
| Development of parameterized cell using Cadence Virtuoso V Borisov East-West Design & Test Symposium (EWDTS 2013), 1-2, 2013 | 8 | 2013 |
| Boxshrink: From bounding boxes to segmentation masks M Gröger, V Borisov, G Kasneci Workshop on Medical Image Learning with Limited and Noisy Data, 65-75, 2022 | 7 | 2022 |
| A novel approach for automatic common-centroid pattern generation V Borisov, K Langner, J Scheible, B Prautsch 2017 14th International Conference on Synthesis, Modeling, Analysis and …, 2017 | 7 | 2017 |
| Microbiome and pancreatic cancer: Time to think about chemotherapy J de Castilhos, K Tillmanns, J Blessing, A Laraño, V Borisov, ... Gut Microbes 16 (1), 2374596, 2024 | 3 | 2024 |
| A robust unsupervised ensemble of feature-based explanations using restricted boltzmann machines V Borisov, J Meier, J Heuvel, H Jalali, G Kasneci XAI4Debugging@NeurIPS2021, 2021 | 3 | 2021 |
| Open Artificial Knowledge V Borisov, RH Schreiber arXiv preprint arXiv:2407.14371, 2024 | 1 | 2024 |
| Relational Local Explanations V Borisov, G Kasneci arXiv preprint arXiv:2212.12374, 2022 | 1 | 2022 |
| Robust deep neural networks for heterogeneous tabular data V Borisov, K Broelemann, E Kasneci, G Kasneci | 1 | 2021 |
| Interpreting Microbiome Relative Abundance Data Using Symbolic Regression S Haldar, C Stein-Thoeringer, V Borisov arXiv preprint arXiv:2410.16109, 2024 | | 2024 |
| Intratumoral microbiome profiles associated with immune tumor microenvironment and genetic alterations of colorectal cancer A Larano, V Borisov, J Schardey, R Yang, K Tillmans, M Illmer, J Andrassy, ... Zeitschrift für Gastroenterologie 62 (09), KV 279, 2024 | | 2024 |
Gjergji KasneciProfessor at the Technical University of Munichtum.de의 이메일 확인됨