Advancing Bayesian Optimization via Learning Correlated Latent Space

31 October 2023

Papers citing "Advancing Bayesian Optimization via Learning Correlated Latent Space"

8 / 8 papers shown

Title
Latent Bayesian Optimization via Autoregressive Normalizing Flows Seunghun Lee Jinyoung Park Jaewon Chu Minseo Yoon H. Kim BDL 30 1 0 21 Apr 2025
A Balanced Approach of Rapid Genetic Exploration and Surrogate Exploitation for Hyperparameter Optimization Chul Kim Inwhee Joe 23 2 0 10 Apr 2025
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences Miguel González Duque Richard Michael Simon Bartels Yevgen Zainchkovskyy Søren Hauberg Wouter Boomsma 42 4 0 07 Jun 2024
Local Latent Space Bayesian Optimization over Structured Inputs N. Maus Haydn Jones Juston Moore Matt J. Kusner John Bradshaw J. Gardner BDL 51 69 0 28 Jan 2022
Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning Lei Tian Yongqiang Tang Liangchen Hu Zhida Ren Wensheng Zhang 35 62 0 20 Mar 2020
Design by adaptive sampling David H. Brookes Jennifer Listgarten TPM 39 65 0 08 Oct 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 203 885 0 07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,338 0 12 Feb 2018