melange:papers:spring2021
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| - | @misc{li2021analytical, | + | @article{10.5555/ |
| + | author = {Bingham, Eli and Chen, Jonathan P. and Jankowiak, Martin and Obermeyer, Fritz and Pradhan, Neeraj and Karaletsos, Theofanis and Singh, Rohit and Szerlip, Paul and Horsfall, Paul and Goodman, Noah D.}, | ||
| + | title = {Pyro: Deep Universal Probabilistic Programming}, | ||
| + | year = {2019}, | ||
| + | issue_date = {January 2019}, | ||
| + | publisher = {JMLR.org}, | ||
| + | volume = {20}, | ||
| + | number = {JMLR}, | ||
| + | issn = {1532-4435}, | ||
| + | loc = {J. Mach. Learn. Res.}, | ||
| + | month = jan, | ||
| + | pages = {973–978}, | ||
| + | numpages = {6}, | ||
| + | keywords = {probabilistic programming, | ||
| + | url = {https:// | ||
| + | } | ||
| + | |||
| + | |||
| + | @article{li2021analytical, | ||
| title={Analytical Characterization and Design Space Exploration for Optimization of CNNs}, | title={Analytical Characterization and Design Space Exploration for Optimization of CNNs}, | ||
| author={Rui Li and Yufan Xu and Aravind Sukumaran-Rajam and Atanas Rountev and P. Sadayappan}, | author={Rui Li and Yufan Xu and Aravind Sukumaran-Rajam and Atanas Rountev and P. Sadayappan}, | ||
| Line 6: | Line 24: | ||
| archivePrefix={arXiv}, | archivePrefix={arXiv}, | ||
| primaryClass={cs.LG}, | primaryClass={cs.LG}, | ||
| - | url={https:// | + | url={https:// |
| + | loc={The ACM Conference on Architectural Support for Programming Languages and Operating | ||
| + | Systems}, | ||
| + | number={ASPLOS} | ||
| } | } | ||
| @article{10.1145/ | @article{10.1145/ | ||
| - | author = {Courant, | + | author = {Courant, |
| title = {Verified Code Generation for the Polyhedral Model}, | title = {Verified Code Generation for the Polyhedral Model}, | ||
| year = {2021}, | year = {2021}, | ||
| Line 24: | Line 45: | ||
| articleno = {40}, | articleno = {40}, | ||
| numpages = {24}, | numpages = {24}, | ||
| - | keywords = {Polyhedral model, Polyhedral code generation, Compiler verification} | + | keywords = {Polyhedral model, Polyhedral code generation, Compiler verification}, |
| + | loc = {Proc. ACM Program. Lang.} | ||
| } | } | ||
| - | Article{Ghahramani2015, | + | @article{Ghahramani2015, |
| author={Ghahramani, | author={Ghahramani, | ||
| title={Probabilistic machine learning and artificial intelligence}, | title={Probabilistic machine learning and artificial intelligence}, | ||
| Line 34: | Line 56: | ||
| month={May}, | month={May}, | ||
| day={01}, | day={01}, | ||
| - | volume={521}, | + | number={521}, |
| - | number={7553}, | + | |
| pages={452-459}, | pages={452-459}, | ||
| issn={1476-4687}, | issn={1476-4687}, | ||
| doi={10.1038/ | doi={10.1038/ | ||
| - | url={https:// | + | url={https:// |
| + | loc={Nature} | ||
| + | } | ||
| + | |||
| + | @article{10.1145/ | ||
| + | author = {Walia, Rajan and Narayanan, Praveen and Carette, Jacques and Tobin-Hochstadt, | ||
| + | title = {From High-Level Inference Algorithms to Efficient Code}, | ||
| + | year = {2019}, | ||
| + | issue_date = {August 2019}, | ||
| + | publisher = {Association for Computing Machinery}, | ||
| + | address = {New York, NY, USA}, | ||
| + | volume = {3}, | ||
| + | number = {ICFP}, | ||
| + | url = {https:// | ||
| + | doi = {10.1145/ | ||
| + | journal = {Proc. ACM Program. Lang.}, | ||
| + | month = jul, | ||
| + | articleno = {98}, | ||
| + | numpages = {30}, | ||
| + | keywords = {loop optimization, | ||
| + | loc = {Proc. ACM Program. Lang.} | ||
| } | } | ||
melange/papers/spring2021.1612792687.txt.gz · Last modified: 2021/02/08 06:58 by lnarmour
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