Kirill Bykov

22 papers A* 3Journal 15Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework.
CoRR
Laura Kopf, Nils Feldhus, Kirill Bykov, Philine Lou Bommer, Anna Hedström, Marina M.-C. Höhne, Oliver Eberle
2025 J jnl
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather.
CoRR
Philine Lou Bommer, Marlene Kretschmer, Fiona R. Spuler, Kirill Bykov, Marina M.-C. Höhne
2025 J jnl
Explaining Bayesian Neural Networks.
Trans. Mach. Learn. Res.
Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft
2024 A* conf
CoSy: Evaluating Textual Explanations of Neurons.
NeurIPS
Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov
2024 J jnl
CoSy: Evaluating Textual Explanations of Neurons.
CoRR
Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov
2024 J jnl
Manipulating Feature Visualizations with Gradient Slingshots.
CoRR
Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Kirill Bykov
2023 J jnl
DORA: Exploring Outlier Representations in Deep Neural Networks.
Trans. Mach. Learn. Res.
Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne
2023 — conf
Finding Spurious Correlations with Function-Semantic Contrast Analysis.
xAI (2)
Kirill Bykov, Laura Kopf, Marina M.-C. Höhne
2023 — conf
GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram.
KaRS@RecSys
Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov
2023 A* conf
Labeling Neural Representations with Inverse Recognition.
NeurIPS
Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne
2023 J jnl
Labeling Neural Representations with Inverse Recognition.
CoRR
Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne
2023 — conf
Mark My Words: Dangers of Watermarked Images in ImageNet.
ECAI Workshops (1)
Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne
2023 J jnl
Mark My Words: Dangers of Watermarked Images in ImageNet.
CoRR
Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne
2023 J jnl
Visualizing the Diversity of Representations Learned by Bayesian Neural Networks.
Trans. Mach. Learn. Res.
Dennis Grinwald, Kirill Bykov, Shinichi Nakajima, Marina M.-C. Höhne
2022 J jnl
DORA: Exploring outlier representations in Deep Neural Networks.
CoRR
Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne
2022 J jnl
DRAMSys4.0: An Open-Source Simulation Framework for In-depth DRAM Analyses.
Int. J. Parallel Program.
Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn
2022 A* conf
NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights.
AAAI
Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne
2022 J jnl
Visualizing the diversity of representations learned by Bayesian neural networks.
CoRR
Dennis Grinwald, Kirill Bykov, Shinichi Nakajima, Marina M.-C. Höhne
2021 J jnl
Explaining Bayesian Neural Networks.
CoRR
Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft
2021 J jnl
NoiseGrad: enhancing explanations by introducing stochasticity to model weights.
CoRR
Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne
2020 — conf
DRAMSys4.0: A Fast and Cycle-Accurate SystemC/TLM-Based DRAM Simulator.
SAMOS
Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn
2020 J jnl
How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks.
CoRR
Kirill Bykov, Marina M.-C. Höhne, Klaus-Robert Müller, Shinichi Nakajima, Marius Kloft