| Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims M Brundage, S Avin, J Wang, H Belfield, K Gretchen, G Hadfield, H Khlaaf, ... https://arxiv.org/abs/2004.07213, 2020 | 427 | 2020 |
| Pysyft: A library for easy federated learning A Ziller, A Trask, A Lopardo, B Szymkow, B Wagner, E Bluemke, ... Federated Learning Systems: Towards Next-Generation AI, 111-139, 2021 | 236 | 2021 |
| Learning patterns of the ageing brain in MRI using deep convolutional networks NK Dinsdale, E Bluemke, SM Smith, Z Arya, D Vidaurre, M Jenkinson, ... NeuroImage 224, 117401, 2021 | 118 | 2021 |
| Rapid detection of necrosis in breast cancer with desorption electrospray ionization mass spectrometry A Tata, M Woolman, M Ventura, N Bernards, M Ganguly, A Gribble, ... Scientific reports 6 (1), 35374, 2016 | 79 | 2016 |
| Optimized Mass Spectrometry Analysis Workflow with Polarimetric Guidance for ex vivo and in situ Sampling of Biological Tissues M Woolman, A Gribble, E Bluemke, J Zou, M Ventura, N Bernards, M Wu, ... Scientific reports 7 (1), 468, 2017 | 56 | 2017 |
| Wide-field tissue polarimetry allows efficient localized mass spectrometry imaging of biological tissues A Tata, A Gribble, M Ventura, M Ganguly, E Bluemke, HJ Ginsberg, ... Chemical science 7 (3), 2162-2169, 2016 | 56 | 2016 |
| Towards best practices in AGI safety and governance: A survey of expert opinion J Schuett, N Dreksler, M Anderljung, D McCaffary, L Heim, E Bluemke, ... arXiv preprint arXiv:2305.07153, 2023 | 43 | 2023 |
| Challenges for machine learning in clinical translation of big data imaging studies NK Dinsdale, E Bluemke, V Sundaresan, M Jenkinson, SM Smith, ... Neuron 110 (23), 3866-3881, 2022 | 39 | 2022 |
| Open-sourcing highly capable foundation models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives E Seger, N Dreksler, R Moulange, E Dardaman, J Schuett, K Wei, ... arXiv preprint arXiv:2311.09227, 2023 | 36 | 2023 |
| An assessment of the utility of tissue smears in rapid cancer profiling with desorption electrospray ionization mass spectrometry (DESI-MS) M Woolman, A Tata, E Bluemke, D Dara, HJ Ginsberg, A Zarrine-Afsar Journal of The American Society for Mass Spectrometry 28 (1), 145-153, 2016 | 34 | 2016 |
| Beyond privacy trade-offs with structured transparency A Trask, E Bluemke, T Collins, BGE Drexler, CG Cuervas-Mons, I Gabriel, ... arXiv preprint arXiv:2012.08347, 2020 | 30 | 2020 |
| Computing Power and the Governance of Artificial Intelligence G Sastry, L Heim, H Belfield, M Anderljung, M Brundage, J Hazell, ... arXiv preprint arXiv:2402.08797, 2024 | 28 | 2024 |
| Toward trustworthy AI development: Mechanisms for supporting verifiable claims. ArXiv M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ... arXiv preprint arXiv:2004.07213, 2020 | 26 | 2020 |
| Orally administered oxygen nanobubbles enhance tumor response to sonodynamic therapy J Owen, K Logan, H Nesbitt, S Able, A Vasilyeva, E Bluemke, ... Nano Select 3 (2), 394-401, 2022 | 20 | 2022 |
| Variations in the abundance of lipid biomarker ions in mass spectrometry images correlate to tissue density J Bilkey, A Tata, TD McKee, AM Porcari, E Bluemke, M Woolman, ... Analytical chemistry 88 (24), 12099-12107, 2016 | 19 | 2016 |
| Towards publicly accountable frontier LLMs: Building an external scrutiny ecosystem under the ASPIRE framework M Anderljung, ET Smith, J O'Brien, L Soder, B Bucknall, E Bluemke, ... arXiv preprint arXiv:2311.14711, 2023 | 16 | 2023 |
| Toward trustworthy AI development: Mechanisms for supporting verifiable claims. arXiv 2020 M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ... arXiv preprint arXiv:2004.07213, 2004 | 16 | 2004 |
| Visibility into AI Agents A Chan, C Ezell, M Kaufmann, K Wei, L Hammond, H Bradley, E Bluemke, ... The 2024 ACM Conference on Fairness, Accountability, and Transparency, 958-973, 2024 | 15 | 2024 |
| Rapid determination of the tumour stroma ratio in squamous cell carcinomas with desorption electrospray ionization mass spectrometry (DESI-MS): a proof-of-concept demonstration M Woolman, A Tata, D Dara, J Meens, E D'Arcangelo, CJ Perez, SS Prova, ... Analyst 142 (17), 3250-3260, 2017 | 15 | 2017 |
| Learning patterns of the ageing brain in MRI using deep convolutional networks. NeuroImage, 224, Article 117401 NK Dinsdale, E Bluemke, SM Smith, Z Arya, D Vidaurre, M Jenkinson, ... | 11 | 2020 |
Arash Zarrine-AfsarUniversity of Toronto/University Health NetworkVerified email at utoronto.ca
