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--- melange:papers:spring2021 [2021/02/08 06:44]
lnarmour
+++ melange:papers:spring2021 [2021/02/08 07:57]
lnarmour
@@ Line 1: / Line 1: @@
+@article{10.5555/3322706.3322734,
+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, deep learning, approximate Bayesian inference, graphical models, generative models},
+url = {https://paperswithcode.com/paper/pyro-deep-universal-probabilistic-programming}
+}
 @misc{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},
-      year={2021},
+year={2021},
-      eprint={2101.09808},
+eprint={2101.09808},
-      archivePrefix={arXiv},
+archivePrefix={arXiv},
-      primaryClass={cs.LG},
+primaryClass={cs.LG},
-      url={https://arxiv.org/pdf/2101.09808.pdf}
+url={https://arxiv.org/pdf/2101.09808.pdf},
+loc={The ACM Conference on Architectural Support for Programming Languages and Operating
+Systems},
+number={ASPLOS}
 }
+@article{10.1145/3434321,
+author = {Courant, Nathanaël and Leroy, Xavier},
+title = {Verified Code Generation for the Polyhedral Model},
+year = {2021},
+issue_date = {January 2021},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+volume = {5},
+number = {POPL},
+url = {https://doi.org/10.1145/3434321},
+doi = {10.1145/3434321},
+journal = {Proc. ACM Program. Lang.},
+month = jan,
+articleno = {40},
+numpages = {24},
+keywords = {Polyhedral model, Polyhedral code generation, Compiler verification},
+loc = {Proc. ACM Program. Lang.}
+}
+@article{Ghahramani2015,
+author={Ghahramani, Zoubin},
+title={Probabilistic machine learning and artificial intelligence},
+journal={Nature},
+year={2015},
+month={May},
+day={01},
+number={521},
+pages={452-459},
+issn={1476-4687},
+doi={10.1038/nature14541},
+url={https://doi.org/10.1038/nature14541},
+loc={Nature}
+}
+@article{10.1145/3341702,
+author = {Walia, Rajan and Narayanan, Praveen and Carette, Jacques and Tobin-Hochstadt, Sam and Shan, Chung-chieh},
+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.org/10.1145/3341702},
+doi = {10.1145/3341702},
+journal = {Proc. ACM Program. Lang.},
+month = jul,
+articleno = {98},
+numpages = {30},
+keywords = {loop optimization, conjugacy, marginalization, collapsed Gibbs sampling, arrays, plates, multidimensional distributions, probabilistic programs, map-reduce},
+loc = {Proc. ACM Program. Lang.}
+}

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