Kirill Bykov

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 18

Top Topics

Watermarked Image

Symbolic Representation

Polyphonic Music

Top Venues

Trans. Mach. Learn. Res.

Publications

Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Kirill Bykov
Manipulating Feature Visualizations with Gradient Slingshots. CoRR (2024)
Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov
CoSy: Evaluating Textual Explanations of Neurons. CoRR (2024)
Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne
Labeling Neural Representations with Inverse Recognition. CoRR (2023)
Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne
Mark My Words: Dangers of Watermarked Images in ImageNet. ECAI Workshops (1) (2023)
Dennis Grinwald, Kirill Bykov, Shinichi Nakajima, Marina M.-C. Höhne
Visualizing the Diversity of Representations Learned by Bayesian Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Kirill Bykov, Laura Kopf, Marina M.-C. Höhne
Finding Spurious Correlations with Function-Semantic Contrast Analysis. xAI (2) (2023)
Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne
Mark My Words: Dangers of Watermarked Images in ImageNet. CoRR (2023)
Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne
DORA: Exploring Outlier Representations in Deep Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne
Labeling Neural Representations with Inverse Recognition. NeurIPS (2023)
Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov
GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram. KaRS@RecSys (2023)
Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn
DRAMSys4.0: An Open-Source Simulation Framework for In-depth DRAM Analyses. Int. J. Parallel Program. 50 (2) (2022)
Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne
DORA: Exploring outlier representations in Deep Neural Networks. CoRR (2022)
Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne
NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights. AAAI (2022)
Dennis Grinwald, Kirill Bykov, Shinichi Nakajima, Marina M.-C. Höhne
Visualizing the diversity of representations learned by Bayesian neural networks. CoRR (2022)
Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft
Explaining Bayesian Neural Networks. CoRR (2021)
Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne
NoiseGrad: enhancing explanations by introducing stochasticity to model weights. CoRR (2021)
Kirill Bykov, Marina M.-C. Höhne, Klaus-Robert Müller, Shinichi Nakajima, Marius Kloft
How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks. CoRR (2020)
Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn
DRAMSys4.0: A Fast and Cycle-Accurate SystemC/TLM-Based DRAM Simulator. SAMOS (2020)