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GAUCHE: A Library for Gaussian Processes in Chemistry

GAUCHE: A Library for Gaussian Processes in Chemistry

6 December 2022
Ryan-Rhys Griffiths
Leo Klarner
Henry B. Moss
Aditya Ravuri
Sang T. Truong
Samuel Stanton
Gary Tom
Bojana Ranković
Yuanqi Du
Arian R. Jamasb
Aryan Deshwal
Julius Schwartz
Austin Tripp
Gregory Kell
Simon Frieder
Anthony Bourached
A. Chan
Jacob Moss
Chengzhi Guo
Johannes Durholt
Saudamini Chaurasia
Felix Strieth-Kalthoff
A. Lee
Bingqing Cheng
Alán Aspuru-Guzik
P. Schwaller
Jian Tang
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Papers citing "GAUCHE: A Library for Gaussian Processes in Chemistry"

13 / 13 papers shown
Title
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
172
0
0
08 Apr 2025
Be aware of overfitting by hyperparameter optimization!
Be aware of overfitting by hyperparameter optimization!
Igor V. Tetko
R. V. Deursen
Guillaume Godin
AI4CE
34
8
0
30 Jul 2024
A survey and benchmark of high-dimensional Bayesian optimization of
  discrete sequences
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
44
4
0
07 Jun 2024
Applications of Gaussian Processes at Extreme Lengthscales: From
  Molecules to Black Holes
Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes
Ryan-Rhys Griffiths
24
1
0
24 Mar 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
Adam X. Yang
Laurence Aitchison
Henry B. Moss
29
4
0
22 Feb 2023
Inducing Point Allocation for Sparse Gaussian Processes in
  High-Throughput Bayesian Optimisation
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
Henry B. Moss
Sebastian W. Ober
Victor Picheny
32
24
0
24 Jan 2023
Controllable Data Generation by Deep Learning: A Review
Controllable Data Generation by Deep Learning: A Review
Shiyu Wang
Yuanqi Du
Xiaojie Guo
Bo Pan
Zhaohui Qin
Liang Zhao
31
28
0
19 Jul 2022
Local Latent Space Bayesian Optimization over Structured Inputs
Local Latent Space Bayesian Optimization over Structured Inputs
Natalie Maus
Haydn Thomas Jones
Juston Moore
Matt J. Kusner
John Bradshaw
Jacob R. Gardner
BDL
51
69
0
28 Jan 2022
Mapping the Space of Chemical Reactions Using Attention-Based Neural
  Networks
Mapping the Space of Chemical Reactions Using Attention-Based Neural Networks
P. Schwaller
Daniel Probst
Alain C. Vaucher
Vishnu H. Nair
D. Kreutter
Teodoro Laino
J. Reymond
147
225
0
09 Dec 2020
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
25
13
0
28 Jun 2020
Gryffin: An algorithm for Bayesian optimization of categorical variables
  informed by expert knowledge
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
Florian Hase
Matteo Aldeghi
Riley J. Hickman
L. Roch
Alán Aspuru-Guzik
47
104
0
26 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes
A Framework for Interdomain and Multioutput Gaussian Processes
Mark van der Wilk
Vincent Dutordoir
S. T. John
A. Artemev
Vincent Adam
J. Hensman
40
94
0
02 Mar 2020
Max-value Entropy Search for Efficient Bayesian Optimization
Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang
Stefanie Jegelka
110
403
0
06 Mar 2017
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