ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2106.03609
  4. Cited By
High-Dimensional Bayesian Optimisation with Variational Autoencoders and
  Deep Metric Learning

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

7 June 2021
Antoine Grosnit
Rasul Tutunov
A. Maraval
Ryan-Rhys Griffiths
Alexander I. Cowen-Rivers
Lin Yang
Lin Zhu
Wenlong Lyu
Zhitang Chen
Jun Wang
Jan Peters
Haitham Bou-Ammar
    BDL
    DRL
ArXivPDFHTML

Papers citing "High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning"

22 / 22 papers shown
Title
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Seunghun Lee
Jinyoung Park
Jaewon Chu
Minseo Yoon
H. Kim
BDL
30
1
0
21 Apr 2025
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
Bojana Ranković
P. Schwaller
BDL
161
0
0
08 Apr 2025
Conditional Latent Space Molecular Scaffold Optimization for Accelerated
  Molecular Design
Conditional Latent Space Molecular Scaffold Optimization for Accelerated Molecular Design
O. Boyar
Hiroyuki Hanada
I. Takeuchi
BDL
40
0
0
03 Nov 2024
Active learning for affinity prediction of antibodies
Active learning for affinity prediction of antibodies
Alexandra Gessner
Sebastian W. Ober
Owen Vickery
Dino Oglic
Talip Uçar
AI4CE
24
4
0
11 Jun 2024
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks
Felix Jimenez
Matthias Katzfuss
BDL
UQCV
61
1
0
26 May 2023
Inverse Protein Folding Using Deep Bayesian Optimization
Inverse Protein Folding Using Deep Bayesian Optimization
N. Maus
Yimeng Zeng
Daniel A. Anderson
Phillip M. Maffettone
Aaron C. Solomon
Peyton Greenside
Osbert Bastani
Jacob R. Gardner
17
2
0
25 May 2023
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with
  Optimized Unlabeled Data Sampling
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
Y. Yin
Yu Wang
Gang Xu
24
4
0
04 May 2023
A dynamic Bayesian optimized active recommender system for
  curiosity-driven Human-in-the-loop automated experiments
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments
Arpan Biswas
Yongtao Liu
Nicole Creange
Yu-Chen Liu
S. Jesse
Jan-Chi Yang
Sergei V. Kalinin
M. Ziatdinov
Rama K Vasudevan
16
5
0
05 Apr 2023
Structured Q-learning For Antibody Design
Structured Q-learning For Antibody Design
Alexander I. Cowen-Rivers
P. Gorinski
Aivar Sootla
Asif R. Khan
Liu Furui
J. Wang
Jan Peters
H. Ammar
OffRL
OnRL
24
3
0
10 Sep 2022
Fast Bayesian Optimization of Needle-in-a-Haystack Problems using
  Zooming Memory-Based Initialization (ZoMBI)
Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization (ZoMBI)
Alexander E. Siemenn
Zekun Ren
Qianxiao Li
Tonio Buonassisi
36
23
0
26 Aug 2022
Bayesian Optimization with Informative Covariance
Bayesian Optimization with Informative Covariance
Afonso Eduardo
Michael U. Gutmann
22
3
0
04 Aug 2022
Optimizing Training Trajectories in Variational Autoencoders via Latent
  Bayesian Optimization Approach
Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach
Arpan Biswas
Rama K Vasudevan
M. Ziatdinov
Sergei V. Kalinin
BDL
DRL
19
10
0
30 Jun 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates
A. Maraval
Matthieu Zimmer
Antoine Grosnit
Rasul Tutunov
Jun Wang
H. Ammar
25
2
0
27 May 2022
Conditional $β$-VAE for De Novo Molecular Generation
Conditional βββ-VAE for De Novo Molecular Generation
Ryan J. Richards
A. Groener
BDL
DRL
22
10
0
01 May 2022
Accelerating Bayesian Optimization for Biological Sequence Design with
  Denoising Autoencoders
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
Samuel Stanton
Wesley J. Maddox
Nate Gruver
Phillip M. Maffettone
E. Delaney
Peyton Greenside
A. Wilson
BDL
31
89
0
23 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs
Local Latent Space Bayesian Optimization over Structured Inputs
N. Maus
Haydn Jones
Juston Moore
Matt J. Kusner
John Bradshaw
J. Gardner
BDL
49
69
0
28 Jan 2022
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via
  Hybrid Action Representation
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Boyan Li
Hongyao Tang
Yan Zheng
Jianye Hao
Pengyi Li
Zhen Wang
Zhaopeng Meng
Li Wang
21
41
0
12 Sep 2021
Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes
Ryan-Rhys Griffiths
Jake L. Greenfield
Aditya R. Thawani
Arian R. Jamasb
Henry B. Moss
Anthony Bourached
Penelope Jones
William McCorkindale
Alexander A. Aldrick
Matthew J. Fuchter Alpha A. Lee
14
13
0
28 Jun 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian
  Optimization
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
Benjamin Letham
Roberto Calandra
Akshara Rai
E. Bakshy
71
109
0
31 Jan 2020
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic
  Bayesian Optimisation
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation
Ryan-Rhys Griffiths
Alexander A. Aldrick
Miguel García-Ortegón
Vidhi R. Lalchand
A. Lee
29
35
0
17 Oct 2019
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation
  Models
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Daniil Polykovskiy
Alexander Zhebrak
Benjamín Sánchez-Lengeling
Sergey Golovanov
Oktai Tatanov
...
Simon Johansson
Hongming Chen
Sergey I. Nikolenko
Alán Aspuru-Guzik
Alex Zhavoronkov
ELM
179
633
0
29 Nov 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
224
1,337
0
12 Feb 2018
1