Jared Roesch

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Tianqi ChenCarnegie Mellon UniversityCorreu electrònic verificat a cmu.edu
Thierry MoreauOctoML Inc., University of WashingtonCorreu electrònic verificat a cs.washington.edu
Luis CezeProfessor of Computer Science and Engineering, University of WashingtonCorreu electrònic verificat a cs.washington.edu
Zachary TatlockUniversity of WashingtonCorreu electrònic verificat a cs.washington.edu
Marisa KirisamePHD Candidate, University of UtahCorreu electrònic verificat a cs.utah.edu
Kyle DeweyAssociate Professor of Computer Science, California State University, NorthridgeCorreu electrònic verificat a csun.edu
Luis VegaUniversity of WashingtonCorreu electrònic verificat a cs.washington.edu
Leonardo de MouraAmazon Web ServicesCorreu electrònic verificat a amazon.com
Jeremy AvigadProfessor of Philosophy and Mathematical Sciences, Carnegie Mellon UniversityCorreu electrònic verificat a cmu.edu
Gabriel EbnerMicrosoft ResearchCorreu electrònic verificat a gebner.org
Arvind KrishnamurthyShort-Dooley Professor, Univ. of WashingtonCorreu electrònic verificat a cs.washington.edu
Lianmin ZhengxAICorreu electrònic verificat a x.ai
Carlos GuestrinProfessor, Stanford UniversityCorreu electrònic verificat a stanford.edu
Lawton NicholsUniversity of California, Santa BarbaraCorreu electrònic verificat a cs.ucsb.edu
Sebastian UllrichKarlsruhe Institute of TechnologyCorreu electrònic verificat a kit.edu
Joseph McMahanUniversity of California, Santa BarbaraCorreu electrònic verificat a cs.ucsb.edu
Dan SuciuUniversity of WashingtonCorreu electrònic verificat a cs.washington.edu
Shumo ChuNEBRA LabsCorreu electrònic verificat a acm.org
Haichen ShenScroll TechCorreu electrònic verificat a scroll.tech
Timothy SherwoodProfessor of Computer Science, UC Santa BarbaraCorreu electrònic verificat a cs.ucsb.edu

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Jared Roesch

OctoML Inc

Correu electrònic verificat a cs.uw.edu - Pàgina d'inici

Programming Languages Machine Learning Verification


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
A hardware–software blueprint for flexible deep learning specialization T Moreau, T Chen, L Vega, J Roesch, E Yan, L Zheng, J Fromm, Z Jiang, ... IEEE Micro 39 (5), 8-16, 2019	199	2019
Relay: A new ir for machine learning frameworks J Roesch, S Lyubomirsky, L Weber, J Pollock, M Kirisame, T Chen, ... Proceedings of the 2nd ACM SIGPLAN international workshop on machine …, 2018	137	2018
A metaprogramming framework for formal verification G Ebner, S Ullrich, J Roesch, J Avigad, L de Moura Proceedings of the ACM on Programming Languages 1 (ICFP), 1-29, 2017	126	2017
Fuzzing the Rust typechecker using CLP (T) K Dewey, J Roesch, B Hardekopf 2015 30th IEEE/ACM International Conference on Automated Software …, 2015	98	2015
Dynamic tensor rematerialization M Kirisame, S Lyubomirsky, A Haan, J Brennan, M He, J Roesch, T Chen, ... arXiv preprint arXiv:2006.09616, 2020	92	2020
Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries S Chu, B Murphy, J Roesch, A Cheung, D Suciu arXiv preprint arXiv:1802.02229, 2018	78	2018
Nimble: Efficiently compiling dynamic neural networks for model inference H Shen, J Roesch, Z Chen, W Chen, Y Wu, M Li, V Sharma, Z Tatlock, ... Proceedings of Machine Learning and Systems 3, 208-222, 2021	61	2021
Language fuzzing using constraint logic programming K Dewey, J Roesch, B Hardekopf Proceedings of the 29th ACM/IEEE international conference on Automated …, 2014	61	2014
Tea: A high-level language and runtime system for automating statistical analysis E Jun, M Daum, J Roesch, S Chasins, E Berger, R Just, K Reinecke Proceedings of the 32nd Annual ACM Symposium on User Interface Software and …, 2019	46	2019
Improved type specialization for dynamic scripting languages MN Kedlaya, J Roesch, B Robatmili, M Reshadi, B Hardekopf Proceedings of the 9th Symposium on Dynamic Languages, 37-48, 2013	35	2013
Relay: A high-level compiler for deep learning J Roesch, S Lyubomirsky, M Kirisame, L Weber, J Pollock, L Vega, ... arXiv preprint arXiv:1904.08368, 2019	32	2019
Relay: A high-level IR for deep learning J Roesch, S Lyubomirsky, M Kirisame, J Pollock, L Weber, Z Jiang, ... arXiv preprint arXiv:1904.08368, 2019	21	2019
Bring your own codegen to deep learning compiler Z Chen, CH Yu, T Morris, J Tuyls, YH Lai, J Roesch, E Delaye, V Sharma, ... arXiv preprint arXiv:2105.03215, 2021	19	2021
Theia: automatically generating correct program state visualizations J Pollock, J Roesch, D Woos, Z Tatlock Proceedings of the 2019 ACM SIGPLAN Symposium on SPLASH-E, 46-56, 2019	11	2019
Relax: composable abstractions for end-to-end dynamic machine learning R Lai, J Shao, S Feng, SS Lyubomirsky, B Hou, W Lin, Z Ye, H Jin, Y Jin, ... arXiv preprint arXiv:2311.02103, 2023	10	2023
Automated data structure generation: Refuting common wisdom K Dewey, L Nichols, B Hardekopf 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering 1 …, 2015	10	2015
An architecture supporting formal and compositional binary analysis J McMahan, M Christensen, L Nichols, J Roesch, SY Guo, B Hardekopf, ... ACM SIGARCH Computer Architecture News 45 (1), 177-191, 2017	9	2017
Optimizing machine learning models M Welsh, J Knight, J Roesch, T Moreau, A Chang, T Chen, LH Ceze, ... US Patent 11,216,752, 2022	3	2022
LastLayer: Toward hardware and software continuous integration L Vega, J Roesch, J McMahan, L Ceze IEEE Micro 40 (4), 103-111, 2020	3	2020
Principled Optimization of Dynamic Neural Networks J Roesch University of Washington, 2020	2	2020

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