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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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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Observation b18c9a70-4e17-4c82-aa0d-a892d3a52ce2 · outbound

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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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

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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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+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

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+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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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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+00:00.

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