Dusenberry, Michael W

8 publications

ICML 2023 A Simple Zero-Shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models James Urquhart Allingham, Jie Ren, Michael W Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan

ICMLW 2023 Morse Neural Networks for Uncertainty Quantification Benoit Dherin, Huiyi Hu, Jie Ren, Michael W Dusenberry, Balaji Lakshminarayanan

AAAI 2023 Neural Spline Search for Quantile Probabilistic Modeling Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister

ICMLW 2022 Plex: Towards Reliability Using Pretrained Large Model Extensions Dustin Tran, Jeremiah Zhe Liu, Michael W Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda E Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, E. Kelly Buchanan, Kevin Patrick Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

NeurIPSW 2022 Reliability Benchmarks for Image Segmentation E. Kelly Buchanan, Michael W Dusenberry, Jie Ren, Kevin Patrick Murphy, Balaji Lakshminarayanan, Dustin Tran

NeurIPSW 2021 Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks Neil Band, Tim G. J. Rudner, Qixuan Feng, Angelos Filos, Zachary Nado, Michael W Dusenberry, Ghassen Jerfel, Dustin Tran, Yarin Gal

ICLR 2021 Combining Ensembles and Data Augmentation Can Harm Your Calibration Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran

CVPRW 2019 Measuring Calibration in Deep Learning Jeremy Nixon, Michael W. Dusenberry, Linchuan Zhang, Ghassen Jerfel, Dustin Tran