There are no reviews yet. Be the first to send feedback to the community and the maintainers!
MACE
code for the ICML2018 paper "Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design"CLaSH-Processor
A simple processor running on FPGA written in Haskell(CLaSH) and compiled into verilogpyMACE
Python implementation of the MACE Bayesian optimization algorithm, with GPy used as the backend GP libraryNeuralLinear
Multi-output Gaussian process regression via multi-task neural networkclash-haskell-fpga
Using CLaSH to run haskell on FPGASparseGP
Sparse Gaussian process: VFE and SVI-GPrecord-vim-time
record how long you have spent on vim per dayBNN
Bayesian neural network implementationsHypervolume-HSO
Calculate hypervolume via Hypervolume by Slicing Objectives(HSO) algorithm.Wrapper_Batch_BO
A simple wrapper of several batch bayesian optimization algorithms(LP,qKG,qEI)priority_queue_haskell_fpga
use CLaSH to describe a priority queue and compile it to verilogMOO
multi-objective optimization via differential evolution and non-dominated sortingMVMO
C++ implementation of the Mean Variance Mapping Optimization algorithmfudanCourseProjectParallelYu
course project and home work of parallel architecture and programmingLove Open Source and this site? Check out how you can help us