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. 2205.13902
  4. Cited By
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates

Sample-Efficient Optimisation with Probabilistic Transformer Surrogates

27 May 2022
A. Maraval
Matthieu Zimmer
Antoine Grosnit
Rasul Tutunov
Jun Wang
H. Ammar
ArXivPDFHTML

Papers citing "Sample-Efficient Optimisation with Probabilistic Transformer Surrogates"

7 / 7 papers shown
Title
PFNs4BO: In-Context Learning for Bayesian Optimization
PFNs4BO: In-Context Learning for Bayesian Optimization
Samuel G. Müller
Matthias Feurer
Noah Hollmann
Frank Hutter
17
33
0
27 May 2023
AntBO: Towards Real-World Automated Antibody Design with Combinatorial
  Bayesian Optimisation
AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation
M. A. Khan
Alexander I. Cowen-Rivers
Antoine Grosnit
Derrick-Goh-Xin Deik
Philippe A. Robert
...
Rasul Tutunov
Dany Bou-Ammar
Jun Wang
Amos Storkey
Haitham Bou-Ammar
40
22
0
29 Jan 2022
Bayesian Transformer Language Models for Speech Recognition
Bayesian Transformer Language Models for Speech Recognition
Boyang Xue
Jianwei Yu
Junhao Xu
Shansong Liu
Shoukang Hu
Zi Ye
Mengzhe Geng
Xunying Liu
H. Meng
BDL
66
24
0
09 Feb 2021
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
64
108
0
31 Jan 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
240
7,597
0
03 Jul 2012
1