AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity | Paper Citation Record

Observation d3603e6d-6c6a-44da-b121-50a7c46e6ae0 · outbound

This paper cites Market drivers for materials and process development in the 21st century,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Market drivers for materials and process development in the 21st century,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.616333Z

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Observation 16b2d5bb-3d56-41d3-ad9d-4f9a88a00d16 · outbound

This paper cites Trial-and-error-based innovation: Rapid materialisation as catalyser of perception and communication in design.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Trial-and-error-based innovation: Rapid materialisation as catalyser of perception and communication in design

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.599463Z

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Observation b2f684c9-55a4-49d3-ba53-24786bf62c83 · outbound

This paper cites Advances and challenges in dft-based energy materials design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Advances and challenges in dft-based energy materials design,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.583931Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 35941335-6abe-4391-aa2c-21b89aaaa1a8 · outbound

This paper cites Materials design and discovery with high-throughput density functional theory: the open quantum materials database (oqmd),.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Materials design and discovery with high-throughput density functional theory: the open quantum materials database (oqmd),

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.568408Z

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Observation 51eb2212-8533-401f-9ae9-3fd3d23acc38 · outbound

This paper cites Combinatorial and high-throughput materials science,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Combinatorial and high-throughput materials science,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.548192Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a373794d-01f1-4b71-9113-f3020d90c8c5 · outbound

This paper cites Mdts: automatic complex materials design using monte carlo tree search,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Mdts: automatic complex materials design using monte carlo tree search,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.532305Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 53f26e41-da25-47fc-b5a0-58a2a4fc923d · outbound

This paper cites Bayesian optimization for materials design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Bayesian optimization for materials design,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.514715Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f0056c1f-793e-4ca3-a9e0-315bf18c893a · outbound

This paper cites Genetic algorithms in materials design and processing,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Genetic algorithms in materials design and processing,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.497708Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e615435-ee75-4d41-97e6-bb77bd074a30 · outbound

This paper cites Materials discovery and design using machine learning,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Materials discovery and design using machine learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.481302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 131fb847-e0f9-42c8-bdc1-d511942fc9ed · outbound

This paper cites Machine learning in materials informatics: recent applications and prospects,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Machine learning in materials informatics: recent applications and prospects,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:01.889160Z

Source-reported events for the cited work

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Observation 5aae7f04-0e36-4e4b-84ef-cfa8c5c57e6c · outbound

This paper cites A generative approach to materials discovery, design, and optimization,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity A generative approach to materials discovery, design, and optimization,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.454287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 23136d23-d3d9-4c39-9fcd-fd2cfd5eeb38 · outbound

This paper cites Generative adversarial networks (gan) based efficient sampling of chemical composition space for inverse design of inorganic materials,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Generative adversarial networks (gan) based efficient sampling of chemical composition space for inverse design of inorganic materials,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.435286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f6700463-41e3-4bc3-a1be-ab36a232b74e · outbound

This paper cites Encoding and exploring latent design space of optimal material structures via a vae-lstm model,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Encoding and exploring latent design space of optimal material structures via a vae-lstm model,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.419027Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7844d83f-58d7-470b-9656-c7d7b8ab9902 · outbound

This paper cites VAE for Modified 1-Hot Generative Materials Modeling, A Step Towards Inverse Material Design.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity VAE for Modified 1-Hot Generative Materials Modeling, A Step Towards Inverse Material Design

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:25:02.510451Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bc70e4a4-4c22-4e70-9078-b48454bf7e8d · outbound

This paper cites A semi-supervised approach to architected materials design using graph neural networks,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity A semi-supervised approach to architected materials design using graph neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.402125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 43195f00-a3dc-4340-98f3-0f09d1839c87 · outbound

This paper cites Inverse design of glass structure with deep graph neural networks,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Inverse design of glass structure with deep graph neural networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.387174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 01cbaa29-df3b-471b-8c23-542c2c824dcc · outbound

This paper cites From small data modeling to large language model screening: A dual-strategy framework for materials intelligent design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity From small data modeling to large language model screening: A dual-strategy framework for materials intelligent design,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.370718Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2229226b-db35-48a1-af24-17f335a8f6e6 · outbound

This paper cites Multi-objective optimization for materials design with improved nsga-ii,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Multi-objective optimization for materials design with improved nsga-ii,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.354849Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d91e1379-11e0-4268-887a-4a651248c320 · outbound

This paper cites A comprehensive survey on nsga-ii for multi- objective optimization and applications,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity A comprehensive survey on nsga-ii for multi- objective optimization and applications,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.337869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4d7e4ba8-b791-466b-8453-eaca0b13d9db · outbound

This paper cites Deep Reinforcement Learning: An Overview.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Deep Reinforcement Learning: An Overview

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:01.950871Z

Source-reported events for the cited work

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Observation 373fc93f-5dc3-4312-ab7d-7917c08c5578 · outbound

This paper cites Deep reinforcement learning for digital materials design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Deep reinforcement learning for digital materials design,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.316662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79ab2185-5bff-4e18-9210-1717c337081f · outbound

This paper cites Deep reinforcement learning for engineering design through topology optimization of elementally discretized design domains,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Deep reinforcement learning for engineering design through topology optimization of elementally discretized design domains,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.298125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 564ef5a4-8951-47d3-8294-83dc4fa9893a · outbound

This paper cites Reinforcement learning applied to metamaterial design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Reinforcement learning applied to metamaterial design,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.280840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c8a2f15c-22d5-46e4-8c3d-13e201427d75 · outbound

This paper cites Deep reinforcement learning for inverse inorganic materials design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Deep reinforcement learning for inverse inorganic materials design,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.264328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bdb117f7-7e16-4b41-a702-fd67bfcacf9e · outbound

This paper cites LLMatDesign: Autonomous Materials Discovery with Large Language Models.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity LLMatDesign: Autonomous Materials Discovery with Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:01.981081Z

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Unavailable: canonical work link unavailable.

Observation c959c75b-2bfc-46d3-aaec-8b37f1ffdb0b · outbound

This paper cites Beyond designer's knowledge: Generating materials design hypotheses via large language models.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Beyond designer's knowledge: Generating materials design hypotheses via large language models

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:25:02.438384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d1691c27-d87c-47b2-bfe7-571f3f42b1d9 · outbound

This paper cites Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:01.995512Z

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Observation bcc5a344-717f-4696-a964-b473f5a04832 · outbound

This paper cites Taking the human out of the loop: A review of bayesian optimization,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Taking the human out of the loop: A review of bayesian optimization,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.239720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 20e04737-7c22-4bea-8e56-dc9e672c7bc4 · outbound

This paper cites A fast and elitist multiobjective genetic algorithm: Nsga-ii,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity A fast and elitist multiobjective genetic algorithm: Nsga-ii,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:02.008529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf97c1ce-15f1-4c69-9b81-274b1e059208 · outbound

This paper cites High-dimensional bayesian optimization for metamaterial design,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity High-dimensional bayesian optimization for metamaterial design,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.207406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c4726f42-9aa7-4245-b400-793ffef92700 · outbound

This paper cites Topology optimization for auxetic metamaterials based on isogeometric analysis,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Topology optimization for auxetic metamaterials based on isogeometric analysis,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.189398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2102c76-c404-46e0-b0bf-52734deac2e3 · outbound

This paper cites Topological optimization design of multi-material phononic crystals with floating projection constraints to achieve ultra-wide band gap,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Topological optimization design of multi-material phononic crystals with floating projection constraints to achieve ultra-wide band gap,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.165302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 63643b51-9cf8-4891-9e61-471e575f6b89 · outbound

This paper cites Introduction to macroscopic optimal design in the mechanics of composite materials and structures,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Introduction to macroscopic optimal design in the mechanics of composite materials and structures,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.146546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7fae7d84-16f2-4471-9e3f-471a32c63cdf · outbound

This paper cites Designing multi-objective multi-armed bandits algorithms: A study,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Designing multi-objective multi-armed bandits algorithms: A study,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.125921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 39a51bc4-d444-4a04-8098-02e5c06d8661 · outbound

This paper cites A machine-learning approach to predicting and under- standing the properties of amorphous metallic alloys,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity A machine-learning approach to predicting and under- standing the properties of amorphous metallic alloys,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.105088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8a4149ea-6948-40c3-8e6c-844f72cfbddf · outbound

This paper cites Logistic regression,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Logistic regression,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.082435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b78ca4c-b7f3-4bfc-ac20-6a5851e47b72 · outbound

This paper cites Linear discriminant analysis,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Linear discriminant analysis,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.054623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 87c7ae05-f439-4a0c-8f18-4cd5bc42e085 · outbound

This paper cites Online training of support vector classifier,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Online training of support vector classifier,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.034656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4218ca46-c815-48c0-834e-bfa33be42abc · outbound

This paper cites Decision tree methods: applications for classification and prediction,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Decision tree methods: applications for classification and prediction,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:03.016493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 359f86ac-e109-4000-982e-43dd66e594ce · outbound

This paper cites Random forests,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Random forests,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:02.075160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2be4f8f-390e-44db-b55f-6090edf7cda4 · outbound

This paper cites Gradient boosting machines, a tutorial,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Gradient boosting machines, a tutorial,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:02.080570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a88ab7fe-7ae1-409a-b132-a5b1afce382f · outbound

This paper cites Xgboost: A scalable tree boosting system,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Xgboost: A scalable tree boosting system,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:02.086108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c301bfa7-30e1-46c7-b9d0-2be5b7c323e9 · outbound

This paper cites Catboost: unbiased boosting with categorical features,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Catboost: unbiased boosting with categorical features,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.956955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6c58b98f-af2a-46c0-af74-f52b07b8ca89 · outbound

This paper cites Multi-class adaboost,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Multi-class adaboost,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.932408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 856ec590-6ce5-4d54-9a5d-86e7d4271a1b · outbound

This paper cites K-nearest neighbors,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity K-nearest neighbors,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.915662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 105e1ce8-c7c0-4836-a9f2-69ea5876a8f0 · outbound

This paper cites Fast gaussian na ¨ ıve bayes for searchlight classification analysis,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Fast gaussian na ¨ ıve bayes for searchlight classification analysis,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.900012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3cd20b34-9953-4fb1-9e01-0dc863d4f11e · outbound

This paper cites Multinomial naive bayes classification model for sentiment analysis,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Multinomial naive bayes classification model for sentiment analysis,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.882975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f1ac6ee3-10df-44d8-a548-571c431a9b4d · outbound

This paper cites Naive bayes classifiers,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Naive bayes classifiers,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.866507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a0d1ac47-c1a4-4c0f-ab7d-0b5d527ced0c · outbound

This paper cites Linear vs. quadratic discriminant analysis classifier: a tutorial,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Linear vs. quadratic discriminant analysis classifier: a tutorial,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.844954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 95e4fca7-48f8-45dc-93e9-f63f744ce66f · outbound

This paper cites Ridge regression,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Ridge regression,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.828395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 39751241-2c68-44c4-90ec-97bcc001441d · outbound

This paper cites Lasso regression,.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Lasso regression,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.810736Z

Source-reported events for the cited work

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Regularization and variable selection via the elastic net,

Reference 52

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Support vector regression,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.781713Z

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Adaboost. rt: a boosting algorithm for regression problems,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.764294Z

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Ensemble deep random vector func- tional link neural network for regression,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.741277Z

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Observation 87c15a29-e640-4640-86c8-18f5304e9c02 · outbound

This paper cites GPT-4o System Card.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity GPT-4o System Card

Reference 56

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Human-level control through deep reinforcement learning,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.722460Z

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Continuous control with deep reinforcement learning

Reference 58

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Addressing function approximation error in actor-critic methods,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:02.190984Z

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Soft Actor-Critic Algorithms and Applications

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T00:25:02.197385Z

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Proximal Policy Optimization Algorithms

Reference 61

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Algorithm as 136: A k-means clustering algorithm,

Reference 62

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Retrieval-augmented generation for knowledge-intensive nlp tasks,

Reference 63

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Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:25:02.658770Z

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Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:25:02.643236Z

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity reward”: Data point’s reward value, [-1, 1], rounded to two decimal places, “reason

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.627817Z

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Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:25:02.612221Z

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Reference 68

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Observation 5706fad8-f3df-4b22-b14e-d0662e93c06f · outbound

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AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity selectedfeatures

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.577768Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bd04fc07-e15a-451b-ad95-d5d3846f811c · outbound

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Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:25:02.559847Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 318236c0-3807-4bfd-9fbb-72964d1ea702 · outbound

This paper cites an unresolved cited work.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:25:02.543505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3dff82ed-f69b-45a2-a07c-f57643be1e99 · outbound

This paper cites selectedfeatures.

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity selectedfeatures

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:25:02.528063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers