Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration | Paper Citation Record

Observation e0423e5d-0772-4ddb-83bf-e4c06022fb0a · outbound

This paper cites Sample efficiency matters: A benchmark for practical molecular optimization, 10 2024.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Sample efficiency matters: A benchmark for practical molecular optimization, 10 2024

Reference 1

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This paper cites Diagnosing and fixing common problems in bayesian optimization for molecule design, 2024.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Diagnosing and fixing common problems in bayesian optimization for molecule design, 2024

Reference 2

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This paper cites Grammar variational autoencoder, 2017.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Grammar variational autoencoder, 2017

Reference 3

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This paper cites Junction tree variational autoencoder for molecular graph generation, 03 2019.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Junction tree variational autoencoder for molecular graph generation, 03 2019

Reference 4

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This paper cites MolGAN: An implicit generative model for small molecular graphs.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration MolGAN: An implicit generative model for small molecular graphs

Reference 5

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This paper cites All smiles variational autoencoder, 06 2019.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration All smiles variational autoencoder, 06 2019

Reference 6

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This paper cites Molecular fingerprint vae, 2021.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Molecular fingerprint vae, 2021

Reference 7

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This paper cites Molecular fingerprints for robust and efficient ml-driven molecular generation, 10 2022.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Molecular fingerprints for robust and efficient ml-driven molecular generation, 10 2022

Reference 8

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This paper cites Barking up the right tree: an approach to search over molecule synthesis dags, 12 2020.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Barking up the right tree: an approach to search over molecule synthesis dags, 12 2020

Reference 9

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This paper cites Local latent space bayesian optimization over structured inputs, 2022.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Local latent space bayesian optimization over structured inputs, 2022

Reference 10

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This paper cites High-dimensional bayesian optimisation with variational autoencoders and deep metric learning, 2021.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration High-dimensional bayesian optimisation with variational autoencoders and deep metric learning, 2021

Reference 11

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This paper cites Gaussian process encoders: Vaes with reliable latent-space uncertainty.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Gaussian process encoders: Vaes with reliable latent-space uncertainty

Reference 12

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This paper cites Molecular de-novo design through deep reinforcement learning.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Molecular de-novo design through deep reinforcement learning

Reference 13

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This paper cites Gflownet foundations, 2021.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Gflownet foundations, 2021

Reference 14

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This paper cites Segler, and Alain C.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Segler, and Alain C

Reference 15

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This paper cites Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design

Reference 16

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Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Unresolved cited work

Reference 17

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This paper cites Parallel and distributed thompson sampling for large-scale accelerated exploration of chemical space.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Parallel and distributed thompson sampling for large-scale accelerated exploration of chemical space

Reference 18

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This paper cites A fresh look at de novo molecular design benchmarks, 05 2023.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration A fresh look at de novo molecular design benchmarks, 05 2023

Reference 19

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Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Unresolved cited work

Reference 20

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Observation f3b6a00c-e557-40f8-9af8-73541cc4fc8e · outbound

This paper cites Timothy Marler and Jasbir S.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Timothy Marler and Jasbir S

Reference 21

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This paper cites The computation of the expected improvement in dominated hypervolume of pareto front approximations, 2008.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration The computation of the expected improvement in dominated hypervolume of pareto front approximations, 2008

Reference 22

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This paper cites Efficient computation of expected hypervolume improvement using box decomposition algorithms.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Efficient computation of expected hypervolume improvement using box decomposition algorithms

Reference 23

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Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Unresolved cited work

Reference 24

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This paper cites Predictive entropy search for multi-objective bayesian optimization.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Predictive entropy search for multi-objective bayesian optimization

Reference 25

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This paper cites Differentiable expected hypervolume improvement for parallel multi-objective bayesian optimization, 2020.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Differentiable expected hypervolume improvement for parallel multi-objective bayesian optimization, 2020

Reference 26

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This paper cites Multi-task gaussian process prediction, 2007.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Multi-task gaussian process prediction, 2007

Reference 27

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This paper cites Kernels for vector-valued functions: a review, 2024.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Kernels for vector-valued functions: a review, 2024

Reference 28

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This paper cites Bohb: Robust and efficient hyperparameter optimization at scale, 07 2018.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Bohb: Robust and efficient hyperparameter optimization at scale, 07 2018

Reference 29

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This paper cites A knowledge-gradient policy for sequential information collection.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration A knowledge-gradient policy for sequential information collection

Reference 30

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This paper cites Wei, David Duvenaud, Jose Miguel Hernandez-Lobato, Benjamin Sanchez-Lengeling, Dennis Sheberia, Jorge Aguilera-Iparraguirre, Timothy D.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Wei, David Duvenaud, Jose Miguel Hernandez-Lobato, Benjamin Sanchez-Lengeling, Dennis Sheberia, Jorge Aguilera-Iparraguirre, Timothy D

Reference 31

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This paper cites A general framework for constrained bayesian optimization using information-based search.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration A general framework for constrained bayesian optimization using information-based search

Reference 32

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Observation e98f83ed-5cfd-40ed-b0d5-9b6cc1e07011 · outbound

This paper cites Deva Priyakumar.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Deva Priyakumar

Reference 33

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This paper cites Graff, Eugene I.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Graff, Eugene I

Reference 34

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This paper cites Swamidass, Hiroto Saigo, and Pierre Baldi.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Swamidass, Hiroto Saigo, and Pierre Baldi

Reference 35

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This paper cites Anderson, G.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Anderson, G

Reference 36

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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This paper cites Smiles, a chemical language and information system.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Smiles, a chemical language and information system

Reference 37

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Observation d7c3565e-85a4-4af2-b554-ca20eb4947ff · outbound

This paper cites Improving fragment-based deep molecular generative models, 07 2024.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Improving fragment-based deep molecular generative models, 07 2024

Reference 38

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This paper cites Therapeutics data commons machine learning datasets and tasks for drug discovery and development, 2021.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Therapeutics data commons machine learning datasets and tasks for drug discovery and development, 2021

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.168545Z

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Observation e86ced9c-7d93-4a46-accd-2884b7e0b7ad · outbound

This paper cites Extended-connectivity fingerprints.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Extended-connectivity fingerprints

Reference 40

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This paper cites Durant, Burton A.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Durant, Burton A

Reference 41

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Observation b278c0d9-8b3e-475f-9fdc-5e6ccbe551bf · outbound

This paper cites jcompoundmapper: An open source java library and command-line tool for chemical fingerprints.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration jcompoundmapper: An open source java library and command-line tool for chemical fingerprints

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.109914Z

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Observation 2c5f15b7-b992-4c11-a3d9-fda2a1cad35c · outbound

This paper cites The pharmacophore kernel for virtual screening with support vector machines.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration The pharmacophore kernel for virtual screening with support vector machines

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.082352Z

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Observation 3f626892-6156-4064-bb28-3f7bcadddbfe · outbound

This paper cites Brown, Shikha Varma-O'Brien, and David Rogers.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Brown, Shikha Varma-O'Brien, and David Rogers

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.067181Z

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Observation 4fb32b68-2c82-45f0-9ea5-2964174b30d8 · outbound

This paper cites Rdkit: A software suite for cheminformatics, computational chemistry, and predictive modeling, 2013.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Rdkit: A software suite for cheminformatics, computational chemistry, and predictive modeling, 2013

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.050270Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 40c8fc13-7bb3-4944-870c-80dcba3daec4 · outbound

This paper cites The photoswitch dataset: A molecular machine learning benchmark for the advancement of synthetic chemistry.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration The photoswitch dataset: A molecular machine learning benchmark for the advancement of synthetic chemistry

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.030021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4842c3ea-e079-4a6e-8ef6-825a3a5c7779 · outbound

This paper cites Population-based de novo molecule generation, using grammatical evolution.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Population-based de novo molecule generation, using grammatical evolution

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:13.007962Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94396da6-4540-4268-9fa8-38ee13cc6009 · outbound

This paper cites Zare, and Patrick Riley.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Zare, and Patrick Riley

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.991488Z

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Observation d6b21425-0100-46f3-ad56-bbbc18f2e13d · outbound

This paper cites Similarity maps - a visualization strategy for molecular fingerprints and machine-learning methods.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Similarity maps - a visualization strategy for molecular fingerprints and machine-learning methods

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.975069Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e2b836b8-a49f-4ed7-b87e-5b8b6b1873d3 · outbound

This paper cites Gaussian processes for machine learning, 2006.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Gaussian processes for machine learning, 2006

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.952050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 581392a2-222e-4c05-9141-bffc0ff1cd2a · outbound

This paper cites Gauche: A library for gaussian processes in chemistry, 2023.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Gauche: A library for gaussian processes in chemistry, 2023

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.919501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 289f1354-108c-4237-97b2-38d330c9c2a4 · outbound

This paper cites An introduction to gaussian process models, 02 2021.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration An introduction to gaussian process models, 02 2021

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.897975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93555fd4-9e45-496a-9394-1eb514fcd7ad · outbound

This paper cites Gaussian process regression networks, 10 2011.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Gaussian process regression networks, 10 2011

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.871439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8e23b04c-2f08-4555-ac7a-c6ef1bbbc941 · outbound

This paper cites Occam's razor, 01 2000.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Occam's razor, 01 2000

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.845525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9afc38f4-3bc6-48cf-a85d-c907f5fb162f · outbound

This paper cites Kernels for graphs.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Kernels for graphs

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.829491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 90422269-4a33-43e0-a3ce-3a96541062c8 · outbound

This paper cites Graph kernels -a synthesis note on positive definiteness graph kernels -a synthesis note on positive definiteness, 2012.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Graph kernels -a synthesis note on positive definiteness graph kernels -a synthesis note on positive definiteness, 2012

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.808082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e1090b2b-c9d2-4b8b-acef-258de10329cb · outbound

This paper cites Graph kernels: a survey.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Graph kernels: a survey

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.786861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2282bfd7-a121-4883-9db7-150fb1391bb8 · outbound

This paper cites Min-max kernels, 2015.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Min-max kernels, 2015

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.766605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e366d7fc-7fdb-4eaf-bdd1-94f5b2a6ef28 · outbound

This paper cites Joshua Swamidass, Jonathan M Chen, Jocelyne Bruand, Peter Phung, Liva Ralaivola, and Pierre Baldi.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Joshua Swamidass, Jonathan M Chen, Jocelyne Bruand, Peter Phung, Liva Ralaivola, and Pierre Baldi

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.745050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa2a9e40-0e0e-4fb8-a8a6-258a6f0752ba · outbound

This paper cites Literature review: Graph kernels in chemoinformatics, 2022.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Literature review: Graph kernels in chemoinformatics, 2022

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.722987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9fc4971e-8566-4a11-a077-9d2046b8d25e · outbound

This paper cites Graph isomorphism in quasipolynomial time, 01 2016.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Graph isomorphism in quasipolynomial time, 01 2016

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.708875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6bf1ea94-50a2-478a-bdca-162aa866a077 · outbound

This paper cites Graph kernels and applications in chemoinformatics, 2007.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Graph kernels and applications in chemoinformatics, 2007

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.688867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d1c917af-f477-4ae3-a2cb-bd807539393a · outbound

This paper cites Introduction to rkhs, and some simple kernel algorithms, 2019.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Introduction to rkhs, and some simple kernel algorithms, 2019

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.661898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cf56aca3-2f14-4c76-a939-f9c470dcd338 · outbound

This paper cites 22 : Hilbert space embeddings of distributions.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration 22 : Hilbert space embeddings of distributions

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.645393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0f245730-9e13-4f2f-8515-2bf0a0c09c82 · outbound

This paper cites Graph kernels for molecular structure-activity relationship analysis with support vector machines.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Graph kernels for molecular structure-activity relationship analysis with support vector machines

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.624399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f3a3bc82-d236-4515-be69-1e425d055177 · outbound

This paper cites an unresolved cited work.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-15T17:37:12.598535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa1361ea-6aac-4b58-b9e7-5acbb1a30cc9 · outbound

This paper cites an elementary mathematical theory of classification and prediction.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration an elementary mathematical theory of classification and prediction

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.579071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cc389c5c-55ae-462c-884e-59f0c831a20c · outbound

This paper cites The hypervolume indicator.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration The hypervolume indicator

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.562697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b4d30526-9772-43ac-9895-2358eb251447 · outbound

This paper cites A multicriteria generalization of bayesian global optimization.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration A multicriteria generalization of bayesian global optimization

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.547608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f3ef9d6-4e3b-469d-9c26-0e607e3d9bf2 · outbound

This paper cites A faster algorithm for calculating hypervolume.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration A faster algorithm for calculating hypervolume

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.526264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 98b31670-1930-45fc-8c14-2bad56e98ce6 · outbound

This paper cites An improved dimension-sweep algorithm for the hypervolume indicator.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration An improved dimension-sweep algorithm for the hypervolume indicator

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.507404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1476ebae-1cb3-44cb-8fe8-df7d333236f5 · outbound

This paper cites Emmerich, K.C.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Emmerich, K.C

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.490374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1bbc4d22-66dc-4a6b-8926-a4d6d7ae650b · outbound

This paper cites Multi-objective bayesian global optimization using expected hypervolume improvement gradient.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Multi-objective bayesian global optimization using expected hypervolume improvement gradient

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.469350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f62b9b65-f475-4858-9838-d2b4eead9546 · outbound

This paper cites Lebesgue measure on the real line, 1997.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Lebesgue measure on the real line, 1997

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.450251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f3f3f510-593d-44d2-8045-cc1f4a575ee1 · outbound

This paper cites The measure of pareto optima applications to multi-objective metaheuristics.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration The measure of pareto optima applications to multi-objective metaheuristics

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.430011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 04e066c7-7cc0-447c-b1ce-7d3badd23497 · outbound

This paper cites Fonseca, and Manuel Lopez-Ibanez.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Fonseca, and Manuel Lopez-Ibanez

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.412136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6c9032ad-31f8-45ac-a552-c41eead21b22 · outbound

This paper cites Chemical substructures that enrich for biological activity.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Chemical substructures that enrich for biological activity

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.395709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6f81a57b-fbbd-4ba1-9821-ad027a21059f · outbound

This paper cites Scikit-fingerprints: easy and efficient computation of molecular fingerprints in python, 07 2024.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Scikit-fingerprints: easy and efficient computation of molecular fingerprints in python, 07 2024

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.375873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c9d94740-d819-4333-9ca6-06311ee07900 · outbound

This paper cites Tripp, Jose Miguel Hernandez-Lobato, Andreas Bender, and Sergio Bacallado.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Tripp, Jose Miguel Hernandez-Lobato, Andreas Bender, and Sergio Bacallado

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.358410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 519c91f8-84a8-415c-b88b-d4bddc28068a · outbound

This paper cites Evaluating predictive uncertainty challenge, 2006.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Evaluating predictive uncertainty challenge, 2006

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.341595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 06f8b2a7-2ba6-439d-977c-d4fba4b2d115 · outbound

This paper cites A new algorithm for adaptive multidimensional integration.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration A new algorithm for adaptive multidimensional integration

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.323298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 37b27055-e4a1-460e-804f-c373b227bb1e · outbound

This paper cites Actually sparse variational gaussian processes, 04 2023.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Actually sparse variational gaussian processes, 04 2023

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.296003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3bd10177-4b25-4ace-af9b-e1c857f2b7c6 · outbound

This paper cites Variational learning of inducing variables in sparse gaussian processes, 04 2009.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Variational learning of inducing variables in sparse gaussian processes, 04 2009

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.280107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be97040d-827e-4fda-b151-eeac6fed1607 · outbound

This paper cites Variational fourier features for gaussian processes.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Variational fourier features for gaussian processes

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.265249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6f43d0f4-3d34-4220-a7e7-a4de35581ffc · outbound

This paper cites Max-value entropy search for multi-objective bayesian optimization.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Max-value entropy search for multi-objective bayesian optimization

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.245773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8494d376-ff59-4a9d-a078-af00c5772cf8 · outbound

This paper cites Unexpected improvements to expected improvement for bayesian optimization, 01 2024.

Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration Unexpected improvements to expected improvement for bayesian optimization, 01 2024

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:37:12.227639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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