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Found 7 papers, 1 papers with code
LinEasyBO: Scalable Bayesian Optimization Approach for Analog Circuit Synthesis via One-Dimensional Subspaces
A large body of literature has proved that the Bayesian optimization framework is especially efficient and effective in analog circuit synthesis.
An Efficient Asynchronous Batch Bayesian Optimization Approach for Analog Circuit Synthesis
A new strategy is proposed to better balance the exploration and exploitation and guarantee the diversity of the query points.
An Efficient Batch Constrained Bayesian Optimization Approach for Analog Circuit Synthesis via Multi-objective Acquisition Ensemble
After achieving the first feasible point, we favor the feasible region by adopting a specially designed penalization term to the acquisition function ensemble.
Deep learning of nanopore sensing signals using a bi-path network
Temporary changes in electrical resistance of a nanopore sensor caused by translocating target analytes are recorded as a sequence of pulses on current traces.
Projection based Active Gaussian Process Regression for Pareto Front Modeling
A novel projection based active Gaussian process regression (P- aGPR) method is proposed for efficient PF modeling.
Bayesian Optimization Approach for Analog Circuit Synthesis Using Neural Network
Bayesian optimization with Gaussian process as surrogate model has been successfully applied to analog circuit synthesis.
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
In each iteration, the multi-objective optimization of the multiple acquisition functions is performed to search for the Pareto front of the acquisition functions.
