Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Adding AE's NeurIPS 2024 papers to papers.md #2673

Closed
wants to merge 1 commit into from
Closed

Adding AE's NeurIPS 2024 papers to papers.md #2673

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 14 additions & 0 deletions docs/papers.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,20 @@ The main reference for BoTorch is

Here is an incomplete selection of peer-reviewed Bayesian optimization papers that build off of BoTorch:

- [Robust Gaussian Processes via Relevance Pursuit](https://arxiv.org/abs/2410.24222). Sebastian Ament, David Eriksson, Elizabeth Santorella, Ben Letham, Max Balandat, Eytan Bakshy. NeurIPS 2024.

- [Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes](https://arxiv.org/abs/2407.09739). Syrine Belakaria, Ben Letham, Janardhan R. Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy. NeurIPS 2024.

- [Approximation-Aware Bayesian Optimization](https://arxiv.org/abs/2406.04308). Natalie Maus, Kyurae Kim, Geoff Pleiss, David Eriksson, John P. Cunningham, Jacob R. Gardner. NeurIPS 2024.

- [Bayesian Optimization of Function Networks with Partial Evaluations](https://arxiv.org/abs/2311.02146). Poompol Buathong, Jiayue Wan, Raul Astudillo, Sam Daulton, Maximilian Balandat, Peter I. Frazier. ICML 2024.

- [Joint Composite Latent Space Bayesian Optimization](https://arxiv.org/abs/2311.02213). Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat, Eytan Bakshy. ICML 2024.

- [Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need](https://arxiv.org/abs/2402.02111). Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Thomas Carlberg, Neil Walton, Kody J. H. Law. ICML 2024.

- [Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences](https://arxiv.org/abs/2306.06296). Michael Shvartsman, Benjamin Letham, Stephen Keeley. UAI 2024.

- [Advancing Bayesian Optimization via Learning Correlated Latent Space](https://arxiv.org/pdf/2310.20258.pdf). Seunghun Lee, Jaewon Chu, Sihyeon Kim, Juyeon Ko, Hyunwoo J. Kim. NeurIPS 2023.

- [Unexpected Improvements to Expected Improvement for Bayesian Optimization](https://arxiv.org/abs/2310.20708). Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy. NeurIPS 2023.
Expand Down
Loading