Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models | Paper Citation Record

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 1

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This paper cites Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, and Zachary Ward Ulissi.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, and Zachary Ward Ulissi

Reference 2

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This paper cites Jaakkola.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Jaakkola

Reference 3

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This paper cites A generative model for inorganic materials design.Nature, 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models A generative model for inorganic materials design.Nature, 2025

Reference 4

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Observation ee3b5a90-6255-4cb3-9370-a65b079634bc · outbound

This paper cites Crystal structure prediction by joint equivariant diffusion.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Crystal structure prediction by joint equivariant diffusion

Reference 5

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Observation f5f0b203-1c4f-4e1d-86cf-8ed561826d26 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 6

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Observation c3e72612-11c9-41c3-8499-5a9c960a5a97 · outbound

This paper cites Fr´echet chemnet distance: A metric for generative models for molecules in drug discovery.Journal of Chemical Information and Modeling, 58(9):1736–1741, 2018.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Fr´echet chemnet distance: A metric for generative models for molecules in drug discovery.Journal of Chemical Information and Modeling, 58(9):1736–1741, 2018

Reference 7

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Observation db6d3443-27f9-4b31-b4f5-fee521e48e5f · outbound

This paper cites Vector field oriented diffusion model for crystal material generation.Proceedings of the AAAI Conference on Artificial Intelligence, 38(20): 22193–22201, Mar.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Vector field oriented diffusion model for crystal material generation.Proceedings of the AAAI Conference on Artificial Intelligence, 38(20): 22193–22201, Mar

Reference 8

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Observation f6b70c9b-f005-4a25-8421-3ca96b755d50 · outbound

This paper cites Jakob, Aron Walsh, Karsten Reuter, and Johannes T.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Jakob, Aron Walsh, Karsten Reuter, and Johannes T

Reference 9

Resolution: verified exact; doi, observed 2026-08-03T17:33:32.321516Z

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Observation a80d6924-06f1-4435-b6ab-073fdaafb741 · outbound

This paper cites Continued challenges in high-throughput materials predictions: Mattergen predicts compounds from the training dataset, 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Continued challenges in high-throughput materials predictions: Mattergen predicts compounds from the training dataset, 2025

Reference 10

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Observation 8aef7bc6-24b4-4979-bc9a-37b0e0f2e31a · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 11

Resolution: verified exact; doi, observed 2026-08-03T17:33:32.126923Z

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Observation 70eaeb97-13f3-41c0-b45b-9fb64db7c920 · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Score-based generative modeling through stochastic differential equations

Reference 12

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Observation ccdaf4fa-7a8b-4af3-a1e3-1b31096869bb · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 13

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Observation f082700b-97c3-4ada-9e99-db7974a7011b · outbound

This paper cites De Gruyter, Berlin, Boston, 2017.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models De Gruyter, Berlin, Boston, 2017

Reference 14

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This paper cites E(n) equivariant graph neural networks.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models E(n) equivariant graph neural networks

Reference 15

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Observation a3f8a77c-20ec-401e-a627-2b78ef7b99cf · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Representation Learning with Contrastive Predictive Coding

Reference 16

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Observation 5dc699f4-7aa6-48c8-b6e9-2008d92fbb1a · outbound

This paper cites Mastej, and Aron Walsh.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Mastej, and Aron Walsh

Reference 17

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 18

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 19

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This paper cites Gleason, Andy Xu, Georgia Channing, Daniel Levy, Ali Ramlaoui, Cl´ementine Fourrier, Chaitanya K.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Gleason, Andy Xu, Georgia Channing, Daniel Levy, Ali Ramlaoui, Cl´ementine Fourrier, Chaitanya K

Reference 20

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 21

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Observation 7e4b2f05-aedc-4a7c-a8da-3b8fd6927a61 · outbound

This paper cites Establishing baselines for generative discovery of inorganic crystals.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Establishing baselines for generative discovery of inorganic crystals

Reference 22

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Observation 9456e187-ea16-4200-a0b8-8f08b81c6421 · outbound

This paper cites Hargreaves, Matthew S.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Hargreaves, Matthew S

Reference 23

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This paper cites Hegde, Kevin V.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Hegde, Kevin V

Reference 24

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Observation 0b9b5098-4033-40fe-9827-776a84f895f1 · outbound

This paper cites Andersson, Abhijith S Parackal, Dong Qian, Rickard Armiento, and Fredrik Lindsten.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Andersson, Abhijith S Parackal, Dong Qian, Rickard Armiento, and Fredrik Lindsten

Reference 25

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This paper cites Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

Reference 26

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This paper cites Understanding and mitigating memorization in generative models via sharpness of probability landscapes.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Understanding and mitigating memorization in generative models via sharpness of probability landscapes

Reference 27

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Observation c6785929-aa83-4bad-8571-1c56fd5584d0 · outbound

This paper cites Score-based generative models detect manifolds.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Score-based generative models detect manifolds

Reference 28

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Observation ba748647-3fb0-4676-a032-442248192517 · outbound

This paper cites An Interpretable Evaluation of Entropy-based Novelty of Generative Models.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models An Interpretable Evaluation of Entropy-based Novelty of Generative Models

Reference 29

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Observation be854441-085d-4d17-ac54-f3d4226a33d3 · outbound

This paper cites Feature likelihood score: Evaluating the generalization of generative models using samples.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Feature likelihood score: Evaluating the generalization of generative models using samples

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T17:30:42.014949Z

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Observation 0a5cd98c-efa2-48b6-91ab-06ed083c1e61 · outbound

This paper cites Density estimation using real NVP.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Density estimation using real NVP

Reference 31

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Observation 1840f5ea-cac4-4a6b-be0d-4f159793b753 · outbound

This paper cites Computational optimal transport: With applications to data science.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Computational optimal transport: With applications to data science

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Observation 038d38f4-0b80-4b42-9aa3-3581f766f613 · outbound

This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.Transactions on Machine Learning Research, 2024.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Improving and generalizing flow-based generative models with minibatch optimal transport.Transactions on Machine Learning Research, 2024

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This paper cites OT-Flow: Fast and accurate continuous normalizing flows via optimal transport.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models OT-Flow: Fast and accurate continuous normalizing flows via optimal transport

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Observation f73ce74e-3992-4451-8ba8-9df159d4a194 · outbound

This paper cites The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009

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Resolution: unresolved; no resolver link, observed 2026-08-03T17:30:42.751931Z

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Observation 313c9f8f-d832-4e31-bd68-4d45e6c90752 · outbound

This paper cites Kipf and Max Welling.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Kipf and Max Welling

Reference 36

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Observation fbe5d37b-c4cd-44e1-a82b-0382837678ff · outbound

This paper cites Wiltschko.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Wiltschko

Reference 37

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Observation bf7a0b24-1376-464b-8882-889b06d20fbf · outbound

This paper cites Schoenholz, Patrick F.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Schoenholz, Patrick F

Reference 38

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Observation b6849daf-0270-4a73-aaf6-b21c933e9576 · outbound

This paper cites Graph Contrastive Learning for Materials.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Graph Contrastive Learning for Materials

Reference 39

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Observation 1e16e2e5-dd1c-41a9-ac0f-76bfd29a0b21 · outbound

This paper cites Csi: Novelty detection via contrastive learning on distributionally shifted instances.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Csi: Novelty detection via contrastive learning on distributionally shifted instances

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Observation 8aca4d7e-bb6b-495a-a104-9f621d4f6fe5 · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

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Observation 717e183a-c4d3-4a8d-b927-7e04bd7f9ca8 · outbound

This paper cites Alaya, Aur˜A©lie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, L˜A©o Gautheron, Nathalie T.H.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Alaya, Aur˜A©lie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, L˜A©o Gautheron, Nathalie T.H

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Observation 34658309-ac9c-4c54-a068-60665505347b · outbound

This paper cites Chevrier, Kristin A.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Chevrier, Kristin A

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Pytorch: An imperative style, high-performance deep learning library

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Observation 7fa8e655-d7df-4137-9286-f47dad3fa12e · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

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Observation 57ad48f4-5873-4589-957e-ee20ad81b2c1 · outbound

This paper cites Lenssen, and Jure Leskovec.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Lenssen, and Jure Leskovec

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Observation 1942cc06-37e0-43df-8965-f1c398d4bce0 · outbound

This paper cites Closed-form diffusion models.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Closed-form diffusion models

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Observation a54f8903-38f5-4b98-92bb-f32d33ad63ed · outbound

This paper cites Diffusion models and the manifold hypothesis: Log-domain smoothing is geometry adaptive.arXiv preprint arXiv:2510.02305, 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Diffusion models and the manifold hypothesis: Log-domain smoothing is geometry adaptive.arXiv preprint arXiv:2510.02305, 2025

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Observation 0d03acc5-bb25-4c6d-9bf8-b88a4d3d371b · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Colocalization for super-resolution microscopy via optimal transport.Nature computational science, 1(3):199–211, 2021

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Observation 7f94ad81-2841-44e5-87dd-b246c83f6767 · outbound

This paper cites On the Edge of Memorization in Diffusion Models.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models On the Edge of Memorization in Diffusion Models

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This paper cites Provable separations between memorization and generalization in diffusion models.arXiv preprint arXiv:2511.03202, 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Provable separations between memorization and generalization in diffusion models.arXiv preprint arXiv:2511.03202, 2025

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Observation 8f4ab5c0-cf92-4092-a3ad-399cce0360e4 · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

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Observation 9b2c773e-3e9c-4258-9000-7ec266960760 · outbound

This paper cites Schnet: A continuous-filter convolutional neural network for modeling quantum interactions.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Schnet: A continuous-filter convolutional neural network for modeling quantum interactions

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Observation 49891f68-85f8-4a88-b398-46965c963827 · outbound

This paper cites Grossman.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Grossman

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Observation 3317d8bc-c831-4882-8c3b-e8b749ad3476 · outbound

This paper cites Cheetham and Ram Seshadri.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Cheetham and Ram Seshadri

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Observation d00619a5-1cb9-4698-9241-8cc72e18d534 · outbound

This paper cites Space group constrained crystal generation.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Space group constrained crystal generation

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This paper cites Exploration of crystal chemical space using text-guided generative artificial intelligence.Nat Commun, 16, 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Exploration of crystal chemical space using text-guided generative artificial intelligence.Nat Commun, 16, 2025

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Observation f46125ee-35b4-47bc-b4b2-457bd87fa1a9 · outbound

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Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

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Resolution: verified exact; doi, observed 2026-08-03T17:33:31.566332Z

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Observation f65492b8-4e00-4b94-a784-74d958264ff3 · outbound

This paper cites Syncotrain: a dual classifier pu-learning framework for synthesizability prediction.Digital Discovery, 4:1437–1448, 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Syncotrain: a dual classifier pu-learning framework for synthesizability prediction.Digital Discovery, 4:1437–1448, 2025

Reference 59

Resolution: verified exact; doi, observed 2026-08-03T17:33:31.322592Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b7bf80bf-774b-4190-8966-6d3f03ef3e54 · outbound

This paper cites A foundation model for atomistic materials chemistry.The Journal of chemical physics, 163(18), 2025.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models A foundation model for atomistic materials chemistry.The Journal of chemical physics, 163(18), 2025

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T17:30:45.497889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec54bd2e-1c53-4020-8ec1-32f965c57db1 · outbound

This paper cites an unresolved cited work.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T17:30:43.835564Z

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Unavailable: canonical work link unavailable.

Observation de86ace4-9569-42b8-8b2b-6b6a361b8591 · outbound

This paper cites an unresolved cited work.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T17:30:41.631865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30c5c4d4-d4d2-4719-8e99-04b6bd85c8fe · outbound

This paper cites an unresolved cited work.

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models Unresolved cited work

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T17:30:40.979895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

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