DRAMSys4.0: A Fast and Cycle-Accurate SystemC/TLM-Based DRAM Simulator. - Lukas Steiner; Matthias Jung 001; Felipe S. Prado; Kirill Bykov; Norbert Wehn (SAMOS, 2020)

How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks. - Kirill Bykov; Marina M.-C. Höhne; Klaus-Robert Müller; Shinichi Nakajima; Marius Kloft (CoRR, 2020)

Explaining Bayesian Neural Networks. - Kirill Bykov; Marina M.-C. Höhne; Adelaida Creosteanu; Klaus-Robert Müller; Frederick Klauschen; Shinichi Nakajima; Marius Kloft (CoRR, 2021)

NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights. - Kirill Bykov; Anna Hedström; Shinichi Nakajima; Marina M.-C. Höhne (AAAI, 2022)

DRAMSys4.0: An Open-Source Simulation Framework for In-depth DRAM Analyses. - Lukas Steiner; Matthias Jung 001; Felipe S. Prado; Kirill Bykov; Norbert Wehn (Int. J. Parallel Program., 2022)

Mark My Words: Dangers of Watermarked Images in ImageNet. - Kirill Bykov; Klaus-Robert Müller; Marina M.-C. Höhne (ECAI Workshops (1), 2023)

GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram. - Oleg Lashinin; Kirill Bykov; Marina Ananyeva; Sergey Kolesnikov (KaRS@RecSys, 2023)

Labeling Neural Representations with Inverse Recognition. - Kirill Bykov; Laura Kopf; Shinichi Nakajima; Marius Kloft; Marina M.-C. Höhne (NeurIPS, 2023)

Finding Spurious Correlations with Function-Semantic Contrast Analysis. - Kirill Bykov; Laura Kopf; Marina M.-C. Höhne (xAI (2), 2023)

DORA: Exploring Outlier Representations in Deep Neural Networks. - Kirill Bykov; Mayukh Deb; Dennis Grinwald; Klaus-Robert Müller; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

Visualizing the Diversity of Representations Learned by Bayesian Neural Networks. - Dennis Grinwald; Kirill Bykov; Shinichi Nakajima; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

CoSy: Evaluating Textual Explanations of Neurons. - Laura Kopf; Philine Lou Bommer; Anna Hedström; Sebastian Lapuschkin; Marina M.-C. Höhne; Kirill Bykov (NeurIPS, 2024)

Manipulating Feature Visualizations with Gradient Slingshots. - Dilyara Bareeva; Marina M.-C. Höhne; Alexander Warnecke; Lukas Pirch; Klaus-Robert Müller; Konrad Rieck; Kirill Bykov (CoRR, 2024)

Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather. - Philine Lou Bommer; Marlene Kretschmer; Fiona R. Spuler; Kirill Bykov; Marina M.-C. Höhne (CoRR, 2025)

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework. - Laura Kopf; Nils Feldhus; Kirill Bykov; Philine Lou Bommer; Anna Hedström; Marina M.-C. Höhne; Oliver Eberle (CoRR, 2025)