David Stutz - RankMe

51 papers A* 9Journal 35Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic. CoRR Peter G. Brodeur, Jacob M. Koshy, Anil Palepu, Khaled Saab, Ava Homiar, Roma Ruparel, Charles Wu, Ryutaro Tanno, Joseph Xu, Amy Wang, David Stutz, Wei-Hung Weng, Hannah M. Ferrera, David G. T. Barrett, Lindsey Crowley, Jihyeon Lee, Spencer E. Rittner, Ellery Wulczyn, Selena K. Zhang, Elahe Vedadi, Christine G. Kohn, Kavita Kulkarni, Vinay Kadiyala, S. Sara Mahdavi, Wendy Du, Jessica M. Williams, David Feinbloom, Renee Wong, Tao Tu, Petar Sirkovic, Alessio Orlandi, Christopher Semturs, Yun Liu, Juraj Gottweis, Dale R. Webster, Joëlle Barral, Katherine Chou, Pushmeet Kohli, Avinatan Hassidim, Yossi Matias, James Manyika, Rob Fields, Jonathan X. Li, Marc L. Cohen, Vivek Natarajan, Mike Schaekermann, Alan Karthikesalingam, Adam Rodman
2026	J	`jnl`	Robust Conformal Prediction for Infrequent Classes. Trans. Mach. Learn. Res. Jens-Michalis Papaioannou, Sebastian Jäger, Alexei Figueroa, David Stutz, Betty van Aken, Keno K. Bressem, Wolfgang Nejdl, Felix A. Gers, Alexander Löser, Felix Biessmann
2025	J	`jnl`	Advancing Conversational Diagnostic AI with Multimodal Reasoning. CoRR Khaled Saab, Jan Freyberg, Chunjong Park, Tim Strother, Yong Cheng, Wei-Hung Weng, David G. T. Barrett, David Stutz, Nenad Tomasev, Anil Palepu, Valentin Liévin, Yash Sharma, Roma Ruparel, Abdullah Ahmed, Elahe Vedadi, Kimberly Kanada, Cían Hughes, Yun Liu, Geoff Brown, Yang Gao, Sean Li, S. Sara Mahdavi, James Manyika, Katherine Chou, Yossi Matias, Avinatan Hassidim, Dale R. Webster, Pushmeet Kohli, S. M. Ali Eslami, Joelle K. Barral, Adam Rodman, Vivek Natarajan, Mike Schaekermann, Tao Tu, Alan Karthikesalingam, Ryutaro Tanno
2025	J	`jnl`	Complementary Human-AI Clinical Reasoning in Ophthalmology. CoRR Mertcan Sevgi, Fares Antaki, Abdullah Zafar Khan, Ariel Yuhan Ong, David Adrian Merle, Kuang Hu, Shafi Balal, Sophie-Christin Kornelia Ernst, Josef Huemer, Gabriel T. Kaufmann, Hagar Khalid, Faye Levina, Celeste Limoli, Ana Paula Ribeiro Reis, Samir Touma, Anil Palepu, Khaled Saab, Ryutaro Tanno, Valentin Liévin, Tao Tu, Yong Cheng, Mike Schaekermann, S. Sara Mahdavi, Elahe Vedadi, David Stutz, Vivek Natarajan, Alan Karthikesalingam, Pearse A. Keane, Wei-Hung Weng
2025	J	`jnl`	Conformalized Credal Regions for Classification with Ambiguous Ground Truth. Trans. Mach. Learn. Res. Michele Caprio, David Stutz, Shuo Li, Arnaud Doucet
2025	J	`jnl`	Evaluating medical AI systems in dermatology under uncertain ground truth. Medical Image Anal. David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam
2025	J	`jnl`	Soft Instruction De-escalation Defense. CoRR Nils Philipp Walter, Chawin Sitawarin, Jamie Hayes, David Stutz, Ilia Shumailov
2025	J	`jnl`	SynthID-Image: Image watermarking at internet scale. CoRR Sven Gowal, Rudy Bunel, Florian Stimberg, David Stutz, Guillermo Ortiz-Jiménez, Christina Kouridi, Mel Vecerík, Jamie Hayes, Sylvestre-Alvise Rebuffi, Paul Bernard, Chris Gamble, Miklós Z. Horváth, Fabian Kaczmarczyck, Alex Kaskasoli, Aleksandar Petrov, Ilia Shumailov, Meghana Thotakuri, Olivia Wiles, Jessica Yung, Zahra Ahmed, Victor Martin, Simon Rosen, Christopher Savcak, Armin Senoner, Nidhi Vyas, Pushmeet Kohli
2025	J	`jnl`	Towards Conversational AI for Disease Management. CoRR Anil Palepu, Valentin Liévin, Wei-Hung Weng, Khaled Saab, David Stutz, Yong Cheng, Kavita Kulkarni, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Katherine Chou, Avinatan Hassidim, Yossi Matias, James Manyika, Ryutaro Tanno, Vivek Natarajan, Adam Rodman, Tao Tu, Alan Karthikesalingam, Mike Schaekermann
2025	J	`jnl`	Towards physician-centered oversight of conversational diagnostic AI. CoRR Elahe Vedadi, David G. T. Barrett, Natalie Harris, Ellery Wulczyn, Shashir Reddy, Roma Ruparel, Mike Schaekermann, Tim Strother, Ryutaro Tanno, Yash Sharma, Jihyeon Lee, Cían Hughes, Dylan Slack, Anil Palepu, Jan Freyberg, Khaled Saab, Valentin Liévin, Wei-Hung Weng, Tao Tu, Yun Liu, Nenad Tomasev, Kavita Kulkarni, S. Sara Mahdavi, Kelvin Guu, Joelle K. Barral, Dale R. Webster, James Manyika, Avinatan Hassidim, Katherine Chou, Yossi Matias, Pushmeet Kohli, Adam Rodman, Vivek Natarajan, Alan Karthikesalingam, David Stutz
2024	J	`jnl`	Capabilities of Gemini Models in Medicine. CoRR Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan
2024	J	`jnl`	Conformalized Credal Regions for Classification with Ambiguous Ground Truth. CoRR Michele Caprio, David Stutz, Shuo Li, Arnaud Doucet
2024	A*	`conf`	Conformalized Credal Set Predictors. NeurIPS Alireza Javanmardi, David Stutz, Eyke Hüllermeier
2024	J	`jnl`	Conformalized Credal Set Predictors. CoRR Alireza Javanmardi, David Stutz, Eyke Hüllermeier
2024	J	`jnl`	Mitigating LLM Hallucinations via Conformal Abstention. CoRR Yasin Abbasi-Yadkori, Ilja Kuzborskij, David Stutz, András György, Adam Fisch, Arnaud Doucet, Iuliya Beloshapka, Wei-Hung Weng, Yao-Yuan Yang, Csaba Szepesvári, Ali Taylan Cemgil, Nenad Tomasev
2024	A*	`conf`	On Adversarial Training without Perturbing all Examples. ICLR Max Maria Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele
2023	—	`conf`	Certified Robust Models with Slack Control and Large Lipschitz Constants. DAGM Max Maria Losch, David Stutz, Bernt Schiele, Mario Fritz
2023	J	`jnl`	Certified Robust Models with Slack Control and Large Lipschitz Constants. CoRR Max Maria Losch, David Stutz, Bernt Schiele, Mario Fritz
2023	J	`jnl`	Conformal prediction under ambiguous ground truth. CoRR David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet
2023	J	`jnl`	Conformal prediction under ambiguous ground truth. Trans. Mach. Learn. Res. David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet
2023	J	`jnl`	Evaluating AI systems under uncertain ground truth: a case study in dermatology. CoRR David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev V. Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam
2023	A*	`conf`	Improving Robustness of Vision Transformers by Reducing Sensitivity to Patch Corruptions. CVPR Yong Guo, David Stutz, Bernt Schiele
2023	J	`jnl`	Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators. IEEE Trans. Pattern Anal. Mach. Intell. David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
2023	A*	`conf`	Robustifying Token Attention for Vision Transformers. ICCV Yong Guo, David Stutz, Bernt Schiele
2023	J	`jnl`	Robustifying Token Attention for Vision Transformers. CoRR Yong Guo, David Stutz, Bernt Schiele
2023	J	`jnl`	Unlocking Accuracy and Fairness in Differentially Private Image Classification. CoRR Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle
2022	J	`jnl`	Improving Corruption and Adversarial Robustness by Enhancing Weak Subnets. CoRR Yong Guo, David Stutz, Bernt Schiele
2022	—	`conf`	Improving Robustness by Enhancing Weak Subnets. ECCV (24) Yong Guo, David Stutz, Bernt Schiele
2022	A*	`conf`	Learning Optimal Conformal Classifiers. ICLR David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
2022	J	`jnl`	On Fragile Features and Batch Normalization in Adversarial Training. CoRR Nils Philipp Walter, David Stutz, Bernt Schiele
2022	—	`—`	Understanding and improving robustness and uncertainty estimation in deep learning. David Stutz
2021	J	`jnl`	A Closer Look at the Adversarial Robustness of Information Bottleneck Models. CoRR Iryna Korshunova, David Stutz, Alexander A. Alemi, Olivia Wiles, Sven Gowal
2021	—	`conf`	Bit Error Robustness for Energy-Efficient DNN Accelerators. MLSys David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
2021	J	`jnl`	Learning Optimal Conformal Classifiers. CoRR David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
2021	J	`jnl`	Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators. CoRR David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
2021	A*	`conf`	Relating Adversarially Robust Generalization to Flat Minima. ICCV David Stutz, Matthias Hein, Bernt Schiele
2021	J	`jnl`	Relating Adversarially Robust Generalization to Flat Minima. CoRR David Stutz, Matthias Hein, Bernt Schiele
2020	—	`conf`	Adversarial Training Against Location-Optimized Adversarial Patches. ECCV Workshops (5) Sukrut Rao, David Stutz, Bernt Schiele
2020	J	`jnl`	Adversarial Training against Location-Optimized Adversarial Patches. CoRR Sukrut Rao, David Stutz, Bernt Schiele
2020	A*	`conf`	Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks. ICML David Stutz, Matthias Hein, Bernt Schiele
2020	J	`jnl`	Learning 3D Shape Completion Under Weak Supervision. Int. J. Comput. Vis. David Stutz, Andreas Geiger
2020	J	`jnl`	On Mitigating Random and Adversarial Bit Errors. CoRR David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
2019	J	`jnl`	Confidence-Calibrated Adversarial Training: Towards Robust Models Generalizing Beyond the Attack Used During Training. CoRR David Stutz, Matthias Hein, Bernt Schiele
2019	A*	`conf`	Disentangling Adversarial Robustness and Generalization. CVPR David Stutz, Matthias Hein, Bernt Schiele
2018	J	`jnl`	Disentangling Adversarial Robustness and Generalization. CoRR David Stutz, Matthias Hein, Bernt Schiele
2018	A*	`conf`	Learning 3D Shape Completion From Laser Scan Data With Weak Supervision. CVPR David Stutz, Andreas Geiger
2018	J	`jnl`	Learning 3D Shape Completion under Weak Supervision. CoRR David Stutz, Andreas Geiger
2018	J	`jnl`	Superpixels: An evaluation of the state-of-the-art. Comput. Vis. Image Underst. David Stutz, Alexander Hermans, Bastian Leibe
2016	J	`jnl`	Superpixels: An Evaluation of the State-of-the-Art. CoRR David Stutz, Alexander Hermans, Bastian Leibe
2015	—	`conf`	Superpixel Segmentation: An Evaluation. GCPR David Stutz
2003	—	`book`	Shared source CLI essentials - exploring Microsoft's Rotor and the ECMA CLI. David Stutz, Ted Neward, Geoff Shilling