Gunes Baydin : Publications
Conference papers
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[1]
Black−Box Optimization with Local Generative Surrogates
Sergey Shirobokov‚ Vladislav Belavin‚ Michael Kagan‚ Andrey Ustyuzhanin and Atılım Güneş Baydin
In Advances in Neural Information Processing Systems 34 (NeurIPS). 2020.
Details about Black−Box Optimization with Local Generative Surrogates | BibTeX data for Black−Box Optimization with Local Generative Surrogates
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[2]
AutoSimulate: (Quickly) Learning Synthetic Data Generation
Harkirat Singh Behl‚ Atılım Güneş Baydin‚ Ran Gal‚ Philip H. S. Torr and Vibhav Vineet
In 16th European Conference on Computer Vision (ECCV). 2020.
Details about AutoSimulate: (Quickly) Learning Synthetic Data Generation | BibTeX data for AutoSimulate: (Quickly) Learning Synthetic Data Generation
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[3]
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin‚ Lei Shao‚ Wahid Bhimji‚ Lukas Heinrich‚ Lawrence F. Meadows‚ Jialin Liu‚ Andreas Munk‚ Saeid Naderiparizi‚ Bradley Gram−Hansen‚ Gilles Louppe‚ Mingfei Ma‚ Xiaohui Zhao‚ Philip Torr‚ Victor Lee‚ Kyle Cranmer‚ Prabhat and Frank Wood
In Proceedings of the International Conference for High Performance Computing‚ Networking‚ Storage and Analysis. New York‚ NY‚ USA. 2019. Association for Computing Machinery.
Details about Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale | BibTeX data for Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale | DOI (10.1145/3295500.3356180) | Link to Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
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[4]
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Atılım Güneş Baydin‚ Lukas Heinrich‚ Wahid Bhimji‚ Lei Shao‚ Saeid Naderiparizi‚ Andreas Munk‚ Jialin Liu‚ Bradley Gram−Hansen‚ Gilles Louppe‚ Lawrence Meadows‚ Philip Torr‚ Victor Lee‚ Prabhat‚ Kyle Cranmer and Frank Wood
In Advances in Neural Information Processing Systems 33 (NeurIPS). 2019.
Details about Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model | BibTeX data for Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
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[5]
Online Learning Rate Adaptation with Hypergradient Descent
Atılım Güneş Baydin‚ Robert Cornish‚ David Martínez Rubio‚ Mark Schmidt and Frank Wood
In Sixth International Conference on Learning Representations (ICLR)‚ Vancouver‚ Canada‚ April 30 – May 3‚ 2018. 2018.
Details about Online Learning Rate Adaptation with Hypergradient Descent | BibTeX data for Online Learning Rate Adaptation with Hypergradient Descent
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[6]
Using Synthetic Data to Train Neural Networks is Model−Based Reasoning
Tuan Anh Le‚ Atılım Güneş Baydin‚ Robert Zinkov and Frank Wood
In 30th International Joint Conference on Neural Networks‚ Anchorage‚ AK‚ USA‚ May 14–19‚ 2017. 2017.
Details about Using Synthetic Data to Train Neural Networks is Model−Based Reasoning | BibTeX data for Using Synthetic Data to Train Neural Networks is Model−Based Reasoning
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[7]
Inference Compilation and Universal Probabilistic Programming
Tuan Anh Le‚ Atılım Güneş Baydin and Frank Wood
In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS). Vol. 54 of Proceedings of Machine Learning Research. Pages 1338–1348. Fort Lauderdale‚ FL‚ USA. 2017. PMLR.
Details about Inference Compilation and Universal Probabilistic Programming | BibTeX data for Inference Compilation and Universal Probabilistic Programming
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[8]
DiffSharp: An AD Library for .NET Languages
Atılım Güneş Baydin‚ Barak A. Pearlmutter and Jeffrey Mark Siskind
In 7th International Conference on Algorithmic Differentiation‚ Christ Church Oxford‚ UK‚ September 12–15‚ 2016. 2016.
Details about DiffSharp: An AD Library for .NET Languages | BibTeX data for DiffSharp: An AD Library for .NET Languages
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[9]
Tricks from Deep Learning
Atılım Güneş Baydin‚ Barak A. Pearlmutter and Jeffrey Mark Siskind
In 7th International Conference on Algorithmic Differentiation‚ Christ Church Oxford‚ UK‚ September 12–15‚ 2016. 2016.
Details about Tricks from Deep Learning | BibTeX data for Tricks from Deep Learning
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[10]
Evolution of ideas: A novel memetic algorithm based on semantic networks
Atılım Güneş Baydin and Ramon López de Mántaras
In Proceedings of the IEEE Congress on Evolutionary Computation‚ CEC 2012‚ IEEE World Congress On Computational Intelligence‚ WCCI 2012‚ Brisbane‚ Australia‚ June 10–15‚ 2012. Pages 1–8. 2012.
Details about Evolution of ideas: A novel memetic algorithm based on semantic networks | BibTeX data for Evolution of ideas: A novel memetic algorithm based on semantic networks | DOI (10.1109/CEC.2012.6252886)