Generalized Rule-Based Fuzzy Cognitive Maps: Structure and Dynamics Model. - Vadim Borisov; Alexander S. Fedulov (ICONIP, 2004)

Development of parameterized cell using Cadence Virtuoso. - Vadim Borisov (EWDTS, 2013)

Linguistic Analysis Based on Fuzzy Similarity Models. - Sergey N. Andreev; Vadim Borisov (Sequences in Language and Text, 2015)

"Compatible" Fuzzy Cognitive Maps for Direct and Inverse Inference. - Vadim Borisov; Alexander S. Fedulov; Yaroslav Fedulov (CompSysTech, 2017)

A novel approach for automatic common-centroid pattern generation. - Vadim Borisov; Kerstin Langner; Jürgen Scheible; Benjamin Prautsch (SMACD, 2017)

Lithography Hotspots Detection Using Deep Learning. - Vadim Borisov; Jürgen Scheible (SMACD, 2018)

Education Quality Evaluation of Electric Power Engineering specialties Students in Technical University of Russia with the Use of Internet Technologies. - A. V. Bobryakov; Vadim Borisov; Yaroslav Fedulov (EAI Endorsed Trans. Energy Web, 2018)

CancelOut: A Layer for Feature Selection in Deep Neural Networks. - Vadim Borisov; Johannes Haug; Gjergji Kasneci (ICANN (2), 2019)

Compositional fuzzy modeling of energy- and resource saving in socio-technical systems. - A. V. Bobryakov; Vadim Borisov; A. I. Gavrilov; E. A. Tikhonova (EAI Endorsed Trans. Energy Web, 2019)

Intelligent Information Search Method Based on a Compositional Ontological Approach. - Vadim Borisov; Dmitry Kotov; Alexander Molyavko (RCAI, 2020)

Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots. - Nikolaos Nikolaou; Ingo P. Waldmann; Angelos Tsiaras; Mario Morvan; Billy Edwards; Kai Hou Yip; Giovanna Tinetti; Subhajit Sarkar; James M. Dawson; Vadim Borisov; Gjergji Kasneci; Matej Petkovic; et al. (CoRR, 2020)

Neuro-Fuzzy Cognitive Temporal Models For Predicting Multidimensional Time Series With Fuzzy Trends. - Vadim Borisov; Victor Luferov (Computación y Sistemas, 2020)

A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines. - Vadim Borisov; Johannes Meier; Johannes van den Heuvel; Hamed Jalali 001; Gjergji Kasneci (CoRR, 2021)

A Consistent and Efficient Evaluation Strategy for Attribution Methods. - Yao Rong; Tobias Leemann; Vadim Borisov; Gjergji Kasneci; Enkelejda Kasneci (ICML, 2022)

BoxShrink: From Bounding Boxes to Segmentation Masks. - Michael Gröger; Vadim Borisov; Gjergji Kasneci (MILLanD@MICCAI, 2022)

Evaluating Feature Attribution: An Information-Theoretic Perspective. - Yao Rong; Tobias Leemann; Vadim Borisov; Gjergji Kasneci; Enkelejda Kasneci (CoRR, 2022)

Relational Local Explanations. - Vadim Borisov; Gjergji Kasneci (CoRR, 2022)

Language Models are Realistic Tabular Data Generators. - Vadim Borisov; Kathrin Seßler; Tobias Leemann; Martin Pawelczyk; Gjergji Kasneci (ICLR, 2023)

Deep Neural Networks and Tabular Data: Inference, Generation, and Explainability. - Vadim Borisov (2023)

DeepTLF: robust deep neural networks for heterogeneous tabular data. - Vadim Borisov; Klaus Broelemann; Enkelejda Kasneci; Gjergji Kasneci (Int. J. Data Sci. Anal., 2023)

Open Artificial Knowledge. - Vadim Borisov; Richard H. Schreiber (CoRR, 2024)

Interpreting Microbiome Relative Abundance Data Using Symbolic Regression. - Swagatam Haldar; Christoph Stein-Thoeringer; Vadim Borisov (CoRR, 2024)

Deep Neural Networks and Tabular Data: A Survey. - Vadim Borisov; Tobias Leemann; Kathrin Seßler; Johannes Haug; Martin Pawelczyk; Gjergji Kasneci (IEEE Trans. Neural Networks Learn. Syst., 2024)