Difference between revisions of "Botorch"
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Latest revision as of 18:11, 22 September 2022
Description
BoTorch is a library for Bayesian Optimization built on PyTorch. BoTorch provides a modular and easily extensible interface for composing Bayesian Optimization primitives, including probabilistic models, acquisition functions, and optimizers.
Environment Modules
Run module spider botorch
to find out what environment modules are available for this application.
System Variables
- HPC_BOTORCH_DIR - installation directory
Citation
If you publish research that uses botorch you have to cite it as follows:
M. Balandat, B. Karrer, D. R. Jiang, S. Daulton, B. Letham, A. G. Wilson, and E. Bakshy. BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. Advances in Neural Information Processing Systems 33, 2020.