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ORCIDGideon Dresdner
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2020 – today
- 2023
[j3]Gideon Dresdner, Dmitrii Kochkov, Peter Christian Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer:
Learning to correct spectral methods for simulating turbulent flows. Trans. Mach. Learn. Res. 2023 (2023)- [i9]Oliver Watt-Meyer, Gideon Dresdner, Jeremy McGibbon, Spencer K. Clark, Brian Henn, James Duncan, Noah D. Brenowitz, Karthik Kashinath, Michael S. Pritchard, Boris Bonev, Matthew E. Peters, Christopher S. Bretherton:
ACE: A fast, skillful learned global atmospheric model for climate prediction. CoRR abs/2310.02074 (2023) - [i8]Prakhar Srivastava, Ruihan Yang, Gavin Kerrigan, Gideon Dresdner, Jeremy McGibbon, Christopher S. Bretherton, Stephan Mandt:
Probabilistic Precipitation Downscaling with Optical Flow-Guided Diffusion. CoRR abs/2312.06071 (2023) - 2022
- [c5]Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher
, Alp Yurtsever:
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. AISTATS 2022: 8439-8457 - [i7]Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever:
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. CoRR abs/2202.13212 (2022) - [i6]Gideon Dresdner, Dmitrii Kochkov, Peter C. Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer:
Learning to correct spectral methods for simulating turbulent flows. CoRR abs/2207.00556 (2022) - 2021
- [j2]Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch:
Sparse Gaussian Processes on Discrete Domains. IEEE Access 9: 76750-76758 (2021) - [c4]Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch:
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. ICML 2021: 11964-11974 - [c3]Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch:
Boosting Variational Inference With Locally Adaptive Step-Sizes. IJCAI 2021: 2337-2343 - [i5]Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch:
Boosting Variational Inference With Locally Adaptive Step-Sizes. CoRR abs/2105.09240 (2021) - [i4]Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch:
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. CoRR abs/2106.05142 (2021) - 2020
- [c2]Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa:
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. ICML 2020: 7253-7262 - [i3]Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Fabian Pedregosa:
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. CoRR abs/2002.11860 (2020)
2010 – 2019
- 2018
- [c1]Francesco Locatello, Gideon Dresdner, Rajiv Khanna, Isabel Valera, Gunnar Rätsch:
Boosting Black Box Variational Inference. NeurIPS 2018: 3405-3415 - [i2]Francesco Locatello, Gideon Dresdner, Rajiv Khanna, Isabel Valera, Gunnar Rätsch:
Boosting Black Box Variational Inference. CoRR abs/1806.02185 (2018) - [i1]Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch:
Scalable Gaussian Processes on Discrete Domains. CoRR abs/1810.10368 (2018) - 2013
- [j1]Bülent Arman Aksoy, Jianjiong Gao, Gideon Dresdner, Weiqing Wang, Alex Root, Xiaohong Jing, Ethan G. Cerami, Chris Sander:
PiHelper: an open source framework for drug-target and antibody-target data. Bioinform. 29(16): 2071-2072 (2013)
Coauthor Index
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