David Stutz

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 36

Top Topics

Top Venues

Publications

Max Maria Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele
On Adversarial Training without Perturbing all Examples. ICLR (2024)
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
Capabilities of Gemini Models in Medicine. CoRR (2024)
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
Mitigating LLM Hallucinations via Conformal Abstention. CoRR (2024)
Alireza Javanmardi, David Stutz, Eyke Hüllermeier
Conformalized Credal Set Predictors. CoRR (2024)
Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle
Unlocking Accuracy and Fairness in Differentially Private Image Classification. CoRR (2023)
Yong Guo, David Stutz, Bernt Schiele
Robustifying Token Attention for Vision Transformers. CoRR (2023)
Yong Guo, David Stutz, Bernt Schiele
Robustifying Token Attention for Vision Transformers. ICCV (2023)
David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet
Conformal prediction under ambiguous ground truth. Trans. Mach. Learn. Res. 2023 (2023)
Yong Guo, David Stutz, Bernt Schiele
Improving Robustness of Vision Transformers by Reducing Sensitivity to Patch Corruptions. CVPR (2023)
David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet
Conformal prediction under ambiguous ground truth. CoRR (2023)
Max Maria Losch, David Stutz, Bernt Schiele, Mario Fritz
Certified Robust Models with Slack Control and Large Lipschitz Constants. CoRR (2023)
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
Evaluating AI systems under uncertain ground truth: a case study in dermatology. CoRR (2023)
David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Max Maria Losch, David Stutz, Bernt Schiele, Mario Fritz
Certified Robust Models with Slack Control and Large Lipschitz Constants. DAGM (2023)
Yong Guo, David Stutz, Bernt Schiele
Improving Corruption and Adversarial Robustness by Enhancing Weak Subnets. CoRR (2022)
Nils Philipp Walter, David Stutz, Bernt Schiele
On Fragile Features and Batch Normalization in Adversarial Training. CoRR (2022)
Yong Guo, David Stutz, Bernt Schiele
Improving Robustness by Enhancing Weak Subnets. ECCV (24) (2022)
David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
Learning Optimal Conformal Classifiers. ICLR (2022)
David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
Bit Error Robustness for Energy-Efficient DNN Accelerators. MLSys (2021)
David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators. CoRR (2021)
Iryna Korshunova, David Stutz, Alexander A. Alemi, Olivia Wiles, Sven Gowal
A Closer Look at the Adversarial Robustness of Information Bottleneck Models. CoRR (2021)
David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
Learning Optimal Conformal Classifiers. CoRR (2021)
David Stutz, Matthias Hein, Bernt Schiele
Relating Adversarially Robust Generalization to Flat Minima. ICCV (2021)
David Stutz, Matthias Hein, Bernt Schiele
Relating Adversarially Robust Generalization to Flat Minima. CoRR (2021)
Sukrut Rao, David Stutz, Bernt Schiele
Adversarial Training Against Location-Optimized Adversarial Patches. ECCV Workshops (5) (2020)
David Stutz, Andreas Geiger
Learning 3D Shape Completion Under Weak Supervision. Int. J. Comput. Vis. 128 (5) (2020)
David Stutz, Matthias Hein, Bernt Schiele
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks. ICML (2020)
Sukrut Rao, David Stutz, Bernt Schiele
Adversarial Training against Location-Optimized Adversarial Patches. CoRR (2020)
David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
On Mitigating Random and Adversarial Bit Errors. CoRR (2020)
David Stutz, Matthias Hein, Bernt Schiele
Confidence-Calibrated Adversarial Training: Towards Robust Models Generalizing Beyond the Attack Used During Training. CoRR (2019)
David Stutz, Matthias Hein, Bernt Schiele
Disentangling Adversarial Robustness and Generalization. CVPR (2019)
David Stutz, Andreas Geiger
Learning 3D Shape Completion under Weak Supervision. CoRR (2018)
David Stutz, Matthias Hein, Bernt Schiele
Disentangling Adversarial Robustness and Generalization. CoRR (2018)
David Stutz, Andreas Geiger
Learning 3D Shape Completion From Laser Scan Data With Weak Supervision. CVPR (2018)
David Stutz, Alexander Hermans, Bastian Leibe
Superpixels: An evaluation of the state-of-the-art. Comput. Vis. Image Underst. 166 (2018)
David Stutz, Alexander Hermans, Bastian Leibe
Superpixels: An Evaluation of the State-of-the-Art. CoRR (2016)
David Stutz
Superpixel Segmentation: An Evaluation. GCPR (2015)