Kirill Bykov

According to our database, Kirill Bykov authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

CoSy: Evaluating Textual Explanations of Neurons.

Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov

CoRR, 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

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

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

Finding Spurious Correlations with Function-Semantic Contrast Analysis.

Kirill Bykov, Laura Kopf, Marina M.-C. Höhne

Proceedings of the Explainable Artificial Intelligence, 2023

Labeling Neural Representations with Inverse Recognition.

Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram.

Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the Fifth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Mark My Words: Dangers of Watermarked Images in ImageNet.

Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne

Proceedings of the Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30, 2023

2022

DRAMSys4.0: An Open-Source Simulation Framework for In-depth DRAM Analyses.

Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn

Int. J. Parallel Program., 2022

NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights.

Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Explaining Bayesian Neural Networks.

Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft

CoRR, 2021

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

DRAMSys4.0: A Fast and Cycle-Accurate SystemC/TLM-Based DRAM Simulator.

Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn

Proceedings of the Embedded Computer Systems: Architectures, Modeling, and Simulation, 2020