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ChemBO: Bayesian Optimization of Small Organic Molecules with
  Synthesizable Recommendations
v1v2 (latest)

ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations

International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
5 August 2019
Ksenia Korovina
Sailun Xu
Kirthevasan Kandasamy
Willie Neiswanger
Barnabás Póczós
J. Schneider
Eric Xing
ArXiv (abs)PDFHTML

Papers citing "ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations"

50 / 78 papers shown
Efficient and Programmable Exploration of Synthesizable Chemical Space
Efficient and Programmable Exploration of Synthesizable Chemical Space
Shitong Luo
Connor W. Coley
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29 Nov 2025
Provable Accelerated Bayesian Optimization with Knowledge Transfer
Provable Accelerated Bayesian Optimization with Knowledge Transfer
Haitao Lin
Boxin Zhao
Mladen Kolar
Chong Liu
175
0
0
05 Nov 2025
Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Haotian Xiang
Jinwen Xu
Qin Lu
281
1
0
01 Oct 2025
BOSfM: A View Planning Framework for Optimal 3D Reconstruction of Agricultural Scenes
BOSfM: A View Planning Framework for Optimal 3D Reconstruction of Agricultural Scenes
Athanasios Bacharis
Konstantinos D. Polyzos
G. Giannakis
Nikolaos Papanikolopoulos
177
1
0
28 Sep 2025
POLO: Preference-Guided Multi-Turn Reinforcement Learning for Lead Optimization
POLO: Preference-Guided Multi-Turn Reinforcement Learning for Lead Optimization
Ziqing Wang
Yibo Wen
William Pattie
Xiao Luo
Weimin Wu
Jerry Yao-Chieh Hu
Abhishek Pandey
Han Liu
Kaize Ding
146
2
0
26 Sep 2025
LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet?
LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet?
Rushil Gupta
Jason Hartford
Bang Liu
BDL
163
2
0
24 Sep 2025
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Richard Cornelius Suwandi
Feng Yin
Juntao Wang
Renjie Li
Tsung-Hui Chang
Sergios Theodoridis
BDL
215
2
0
22 Sep 2025
Exploring Synthesizable Chemical Space with Iterative Pathway Refinements
Exploring Synthesizable Chemical Space with Iterative Pathway Refinements
Seul Lee
Karsten Kreis
Srimukh Prasad Veccham
Meng Liu
Danny Reidenbach
Saee Paliwal
Weili Nie
Arash Vahdat
LRMAI4CE
272
4
0
19 Sep 2025
Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?Conference on Uncertainty in Artificial Intelligence (UAI), 2025
Hwanwoo Kim
Chong Liu
Yuxin Chen
394
4
0
13 Jun 2025
LLINBO: Trustworthy LLM-in-the-Loop Bayesian Optimization
LLINBO: Trustworthy LLM-in-the-Loop Bayesian Optimization
Chih-Yu Chang
Milad Azvar
Chinedum Okwudire
Raed Al Kontar
UQCV
429
5
0
20 May 2025
LLM-Augmented Chemical Synthesis and Design Decision Programs
LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang
Jeff Guo
Lingkai Kong
R. Ramprasad
Philippe Schwaller
Yuanqi Du
Chao Zhang
298
8
0
11 May 2025
Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models
Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process ModelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Mingyu Pu
Songhao Wang
Haowei Wang
Szu Hui Ng
263
0
0
04 Mar 2025
Quantum Non-Linear Bandit Optimization
Quantum Non-Linear Bandit Optimization
Zakaria Shams Siam
Chaowen Guan
Chong Liu
447
3
0
04 Mar 2025
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
InversionGNN: A Dual Path Network for Multi-Property Molecular OptimizationInternational Conference on Learning Representations (ICLR), 2025
Yifan Niu
Ziqi Gao
Qifeng Bai
Yang Liu
Yatao Bian
Yu Rong
Junzhou Huang
Jia Li
324
2
0
03 Mar 2025
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
A. Adibi
Xu Cao
Zongliang Ji
Jivat Neet Kaur
Winston Chen
...
Mohsen Sadatsafavi
Dennis L. Shung
Shannon McWeeney
Jessica Dafflon
Sarah Jabbour
OODVLMAI4TS
459
1
0
10 Feb 2025
Challenging reaction prediction models to generalize to novel chemistry
Challenging reaction prediction models to generalize to novel chemistryACS Central Science (ACS Cent. Sci.), 2025
John Bradshaw
Anji Zhang
Babak Mahjour
David E. Graff
Marwin H. S. Segler
Connor W. Coley
229
10
0
11 Jan 2025
Generative Artificial Intelligence for Navigating Synthesizable Chemical
  Space
Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
Wenhao Gao
Shitong Luo
Connor W. Coley
282
20
0
04 Oct 2024
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein DesignInternational Conference on Learning Representations (ICLR), 2024
Melis Ilayda Bal
Pier Giuseppe Sessa
Mojmír Mutný
Andreas Krause
438
2
0
27 Sep 2024
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
415
2
0
02 Sep 2024
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional
  Search
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
Kevin Yu
Jihye Roh
Ziang Li
Wenhao Gao
Runzhong Wang
Connor W. Coley
376
23
0
08 Jul 2024
Graph Neural Thompson Sampling
Graph Neural Thompson Sampling
Shuang Wu
Arash A. Amini
400
1
0
15 Jun 2024
FunBO: Discovering Acquisition Functions for Bayesian Optimization with
  FunSearch
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
Virginia Aglietti
Ira Ktena
Jessica Schrouff
Eleni Sgouritsa
Francisco J. R. Ruiz
Alan Malek
Alexis Bellot
Silvia Chiappa
328
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07 Jun 2024
RGFN: Synthesizable Molecular Generation Using GFlowNets
RGFN: Synthesizable Molecular Generation Using GFlowNets
Michal Koziarski
Andrei Rekesh
Dmytro Shevchuk
A. V. D. Sloot
Piotr Gaiñski
Yoshua Bengio
Cheng-Hao Liu
Mike Tyers
Robert A. Batey
285
39
0
01 Jun 2024
Bayesian Optimization of Functions over Node Subsets in Graphs
Bayesian Optimization of Functions over Node Subsets in Graphs
Huidong Liang
Xingchen Wan
Xiaowen Dong
454
3
0
24 May 2024
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
M. Cretu
Charles Harris
Julien Roy
Emmanuel Bengio
Pietro Lio
Bruno Correia
Julien Roy
Emmanuel Bengio
Pietro Liò
488
4
0
02 May 2024
A Sober Look at LLMs for Material Discovery: Are They Actually Good for
  Bayesian Optimization Over Molecules?
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi
Felix Strieth-Kalthoff
Marta Skreta
Pascal Poupart
Alán Aspuru-Guzik
Geoff Pleiss
413
49
0
07 Feb 2024
Large Language Models to Enhance Bayesian Optimization
Large Language Models to Enhance Bayesian OptimizationInternational Conference on Learning Representations (ICLR), 2024
Tennison Liu
Nicolás Astorga
Nabeel Seedat
M. Schaar
451
140
0
06 Feb 2024
PG-LBO: Enhancing High-Dimensional Bayesian Optimization with
  Pseudo-Label and Gaussian Process Guidance
PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance
Taicai Chen
Yue Duan
Dong Li
Lei Qi
Yinghuan Shi
Yang Gao
BDLDRL
248
11
0
28 Dec 2023
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian
  Regret Bounds
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret BoundsInternational Conference on Machine Learning (ICML), 2023
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
Ichiro Takeuchi
483
13
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07 Nov 2023
Advancing Bayesian Optimization via Learning Correlated Latent Space
Advancing Bayesian Optimization via Learning Correlated Latent SpaceNeural Information Processing Systems (NeurIPS), 2023
Seunghun Lee
Jaewon Chu
S. Kim
Juyeon Ko
Hyunwoo J. Kim
BDL
571
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31 Oct 2023
Molecular De Novo Design through Transformer-based Reinforcement
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Molecular De Novo Design through Transformer-based Reinforcement Learning
Pengcheng Xu
Tao Feng
Tianfan Fu
Siddhartha Laghuvarapu
Jimeng Sun
612
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09 Oct 2023
3D Reconstruction in Noisy Agricultural Environments: A Bayesian
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3D Reconstruction in Noisy Agricultural Environments: A Bayesian Optimization Perspective for View Planning
Athanasios Bacharis
Konstantinos D. Polyzos
H. J. Nelson
G. Giannakis
Nikolaos Papanikolopoulos
356
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Efficient Bayesian Optimization with Deep Kernel Learning and
  Transformer Pre-trained on Multiple Heterogeneous Datasets
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Zhitang Chen
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Amortized Inference for Gaussian Process Hyperparameters of Structured
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Pierre Osselin
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Symmetric Replay Training: Enhancing Sample Efficiency in Deep
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Jinkyoo Park
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Learning Relevant Contextual Variables Within Bayesian Optimization
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Samuel Kaski
399
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Yiran Zhou
Liangren Zhang
Yuheng Ding
Ningfeng Liu
Song Song
L. Zhang
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Zhenming Liu
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Deep Learning Methods for Small Molecule Drug Discovery: A Survey
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Yingying Liu
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Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian
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Yu Inatsu
Masayuki Karasuyama
317
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