Search Results - "Bielik, Pavol"

Machine Learning for Health: Algorithm Auditing & Quality Control by Oala, Luis, Murchison, Andrew G., Balachandran, Pradeep, Choudhary, Shruti, Fehr, Jana, Leite, Alixandro Werneck, Goldschmidt, Peter G., Johner, Christian, Schörverth, Elora D. M., Nakasi, Rose, Meyer, Martin, Cabitza, Federico, Baird, Pat, Prabhu, Carolin, Weicken, Eva, Liu, Xiaoxuan, Wenzel, Markus, Vogler, Steffen, Akogo, Darlington, Alsalamah, Shada, Kazim, Emre, Koshiyama, Adriano, Piechottka, Sven, Macpherson, Sheena, Shadforth, Ian, Geierhofer, Regina, Matek, Christian, Krois, Joachim, Sanguinetti, Bruno, Arentz, Matthew, Bielik, Pavol, Calderon-Ramirez, Saul, Abbood, Auss, Langer, Nicolas, Haufe, Stefan, Kherif, Ferath, Pujari, Sameer, Samek, Wojciech, Wiegand, Thomas

“…Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is…”
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Adversarial Robustness for Code by Bielik, Pavol, Vechev, Martin

“…Machine learning and deep learning in particular has been recently used to successfully address many tasks in the domain of code such as finding and fixing…”
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Learning to Infer User Interface Attributes from Images by Schlattner, Philippe, Bielik, Pavol, Vechev, Martin

“…We explore a new domain of learning to infer user interface attributes that helps developers automate the process of user interface implementation. Concretely,…”
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COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act by Guldimann, Philipp, Spiridonov, Alexander, Staab, Robin, Jovanović, Nikola, Vero, Mark, Vechev, Velko, Gueorguieva, Anna, Balunović, Mislav, Konstantinov, Nikola, Bielik, Pavol, Tsankov, Petar, Vechev, Martin

“…The EU's Artificial Intelligence Act (AI Act) is a significant step towards responsible AI development, but lacks clear technical interpretation, making it…”
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Automated Discovery of Adaptive Attacks on Adversarial Defenses by Yao, Chengyuan, Bielik, Pavol, Tsankov, Petar, Vechev, Martin

“…Reliable evaluation of adversarial defenses is a challenging task, currently limited to an expert who manually crafts attacks that exploit the defense's inner…”
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Adversarial Attacks on Probabilistic Autoregressive Forecasting Models by Dang-Nhu, Raphaël, Singh, Gagandeep, Bielik, Pavol, Vechev, Martin

“…We develop an effective generation of adversarial attacks on neural models that output a sequence of probability distributions rather than a sequence of single…”
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Robustness testing of AI systems: A case study for traffic sign recognition by Berghoff, Christian, Bielik, Pavol, Neu, Matthias, Tsankov, Petar, von Twickel, Arndt

“…In: Maglogiannis I., Macintyre J., Iliadis L. (eds) Artificial Intelligence Applications and Innovations. AIAI 2021. IFIP Advances in Information and…”
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Toward Mission-Critical AI: Interpretable, Actionable, and Resilient AI by Linkov, Igor, Stoddard, Kelsey, Strelzoff, Andrew, Galaitsi, S.E., Keisler, Jeffrey, Trump, Benjamin D., Kott, Alexander, Bielik, Pavol, Tsankov, Petar

“…Artificial intelligence (AI) is widely used in science and practice. However, its use in mission-critical contexts is limited due to the lack of appropriate…”
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Learning a Static Analyzer from Data by Bielik, Pavol, Raychev, Veselin, Vechev, Martin

“…To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by…”
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