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Paper Citation Record · LEDGER

OpenQDC: Open Quantum Data Commons

As of 20 August 2026, this Paper Citation Record lists 100 of 117 outbound references and 0 inbound Pith citation observations for arXiv:2411.19629.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.19629 v1

Coverage vector

measured 100 of 117 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T06:01:04.750870Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 117 outbound references displayed

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  • verified fuzzy37
  • unresolved62
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5648ffcf-8119-4409-8ddc-fcb1a6eb827b · outbound

This paper cites Computational approaches for studying drug binding kinetics.

OpenQDC: Open Quantum Data Commons Computational approaches for studying drug binding kinetics

Reference 1

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Observation 4ca59b64-f4bf-43ad-8757-62ee3032496d · outbound

This paper cites Protein–ligand (un) binding kinetics as a new paradigm for drug discovery at the crossroad between experiments and modelling.

OpenQDC: Open Quantum Data Commons Protein–ligand (un) binding kinetics as a new paradigm for drug discovery at the crossroad between experiments and modelling

Reference 2

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Observation 7d4fe19f-c70f-46a2-8e18-7f669fb2c211 · outbound

This paper cites New approaches for computing ligand–receptor binding kinetics.

OpenQDC: Open Quantum Data Commons New approaches for computing ligand–receptor binding kinetics

Reference 3

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Observation b121ac96-d0d6-4797-ad59-754f91a1b0b5 · outbound

This paper cites Kinetics of ligand–protein dissociation from all-atom simulations: Are we there yet? Biochemistry, 58(3):156–165, 2018.

OpenQDC: Open Quantum Data Commons Kinetics of ligand–protein dissociation from all-atom simulations: Are we there yet? Biochemistry, 58(3):156–165, 2018

Reference 4

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Observation ec04c268-4add-4335-a483-6bd51c4f4466 · outbound

This paper cites Molecular dynamics simulations in drug design.

OpenQDC: Open Quantum Data Commons Molecular dynamics simulations in drug design

Reference 5

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Observation 234024a2-a498-44e7-9679-4af8cd38725d · outbound

This paper cites Molecular dynamics and protein function.

OpenQDC: Open Quantum Data Commons Molecular dynamics and protein function

Reference 6

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Observation 8239e88e-ddb1-4f06-8cf8-733b655ce0cd · outbound

This paper cites Applications of molecular dynamics simulation in protein study.

OpenQDC: Open Quantum Data Commons Applications of molecular dynamics simulation in protein study

Reference 7

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Observation ea02842e-d4af-48c7-acf3-70c1f3073647 · outbound

This paper cites Gfn2-xtb—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions.

OpenQDC: Open Quantum Data Commons Gfn2-xtb—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions

Reference 8

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Observation 7d14d0ad-80c9-4f3b-837a-c1138325b1cd · outbound

This paper cites Dftb3: Extension of the self-consistent- charge density-functional tight-binding method (scc-dftb).

OpenQDC: Open Quantum Data Commons Dftb3: Extension of the self-consistent- charge density-functional tight-binding method (scc-dftb)

Reference 9

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Observation 1c853003-5fdb-4767-866b-51a2de150405 · outbound

This paper cites Optimization of parameters for semiempirical methods v: Modification of nddo approximations and application to 70 elements.

OpenQDC: Open Quantum Data Commons Optimization of parameters for semiempirical methods v: Modification of nddo approximations and application to 70 elements

Reference 10

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Observation 968eeab6-4e53-47d7-9a4f-4dfa405bc321 · outbound

This paper cites Generalized neural-network representation of high- dimensional potential-energy surfaces.

OpenQDC: Open Quantum Data Commons Generalized neural-network representation of high- dimensional potential-energy surfaces

Reference 11

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Observation beea93f7-2540-406f-a11a-38911fe6d189 · outbound

This paper cites Ani-1, a data set of 20 million calculated off-equilibrium conformations for organic molecules.

OpenQDC: Open Quantum Data Commons Ani-1, a data set of 20 million calculated off-equilibrium conformations for organic molecules

Reference 12

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Observation f79e9934-f8b4-4857-a60e-c71575f7389f · outbound

This paper cites Amp: A modular approach to machine learning in atomistic simulations.

OpenQDC: Open Quantum Data Commons Amp: A modular approach to machine learning in atomistic simulations

Reference 13

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Observation f5d5e281-7d76-4855-a4d3-45bfc2344e7f · outbound

This paper cites A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information.

OpenQDC: Open Quantum Data Commons A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

Reference 14

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Observation e0b92d3d-b507-495a-a593-55e89fe6a8eb · outbound

This paper cites Equivariant transformers for neural network based molecular potentials.

OpenQDC: Open Quantum Data Commons Equivariant transformers for neural network based molecular potentials

Reference 15

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Observation 77729bcb-495d-4083-920d-ec81eb5e72e2 · outbound

This paper cites Linear atomic cluster expansion force fields for organic molecules: beyond rmse.

OpenQDC: Open Quantum Data Commons Linear atomic cluster expansion force fields for organic molecules: beyond rmse

Reference 16

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Observation e4c61e39-1cdd-485a-9d5b-57d7911ffb20 · outbound

This paper cites Efficient and accurate machine- learning interpolation of atomic energies in compositions with many species.

OpenQDC: Open Quantum Data Commons Efficient and accurate machine- learning interpolation of atomic energies in compositions with many species

Reference 17

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Observation f48b7d9e-b363-45c4-96ca-a56e6b1b7c7c · outbound

This paper cites Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements.

OpenQDC: Open Quantum Data Commons Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements

Reference 18

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Observation 8cf8008c-de4a-47d4-b056-09c5b57c792a · outbound

This paper cites Directional Message Passing for Molecular Graphs.

OpenQDC: Open Quantum Data Commons Directional Message Passing for Molecular Graphs

Reference 19

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Observation 1063556b-32c1-47a4-912a-51b9fe834649 · outbound

This paper cites Gemnet: Universal directional graph neural networks for molecules.

OpenQDC: Open Quantum Data Commons Gemnet: Universal directional graph neural networks for molecules

Reference 20

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Observation d6fcaa2b-c1cd-4805-bb13-dab383f96def · outbound

This paper cites Spherical message passing for 3d molecular graphs.

OpenQDC: Open Quantum Data Commons Spherical message passing for 3d molecular graphs

Reference 21

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Observation 09aa2b09-f45e-4313-9867-9adbfc0b2cef · outbound

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

OpenQDC: Open Quantum Data Commons E (n) equivariant graph neural networks

Reference 22

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Observation 64d5d06e-7654-40bb-a20f-d1014320baea · outbound

This paper cites A universal graph deep learning interatomic potential for the periodic table.

OpenQDC: Open Quantum Data Commons A universal graph deep learning interatomic potential for the periodic table

Reference 23

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Observation 0a630d37-f488-4f51-81ab-6b4111d41e89 · outbound

This paper cites Equivariant message passing for the prediction of tensorial properties and molecular spectra.

OpenQDC: Open Quantum Data Commons Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 24

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Observation 2f40e311-05a2-4e68-81f9-058a7b41776d · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

OpenQDC: Open Quantum Data Commons Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 25

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Observation 63bae921-648a-44c3-95cc-0be3247909f8 · outbound

This paper cites Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry.

OpenQDC: Open Quantum Data Commons Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry

Reference 26

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Observation 01a37351-6dae-428b-9047-ed0b9e066632 · outbound

This paper cites Ani-1: an extensible neural network potential with dft accuracy at force field computational cost.

OpenQDC: Open Quantum Data Commons Ani-1: an extensible neural network potential with dft accuracy at force field computational cost

Reference 27

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Observation 0f6633c1-79d9-4996-8091-6cd03a88cd23 · outbound

This paper cites Torchani: A free and open source pytorch-based deep learning implementation of the ani neural network potentials.

OpenQDC: Open Quantum Data Commons Torchani: A free and open source pytorch-based deep learning implementation of the ani neural network potentials

Reference 28

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Observation 7e9108c9-0e3a-4d2b-9883-4cb2d951eff8 · outbound

This paper cites Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network.

OpenQDC: Open Quantum Data Commons Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network

Reference 29

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Observation 0c970b5a-ee63-4d40-aeda-90c0e6a1b4d7 · outbound

This paper cites Aimnet2: a neural network potential to meet your neutral, charged, organic, and elemental-organic needs.

OpenQDC: Open Quantum Data Commons Aimnet2: a neural network potential to meet your neutral, charged, organic, and elemental-organic needs

Reference 30

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Observation 411ac351-f6d3-48cf-a5c3-a9da88245a43 · outbound

This paper cites MACE-OFF: Transferable Short Range Machine Learning Force Fields for Organic Molecules.

OpenQDC: Open Quantum Data Commons MACE-OFF: Transferable Short Range Machine Learning Force Fields for Organic Molecules

Reference 31

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Observation 7d242368-120e-4f6a-a79c-fa6e6db11c71 · outbound

This paper cites Forces are not enough: Benchmark and critical evaluation for machine learning force fields with molecular simulations.

OpenQDC: Open Quantum Data Commons Forces are not enough: Benchmark and critical evaluation for machine learning force fields with molecular simulations

Reference 32

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Observation cf3c6074-784c-4aa6-9fe2-31d4a43b40c8 · outbound

This paper cites Scalable bayesian uncertainty quantifi- cation for neural network potentials: Promise and pitfalls.

OpenQDC: Open Quantum Data Commons Scalable bayesian uncertainty quantifi- cation for neural network potentials: Promise and pitfalls

Reference 33

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Observation 471fb39b-2a6a-4817-bce5-ae301db93853 · outbound

This paper cites Molecular dynamics simulations with quantum mechanics/molec- ular mechanics and adaptive neural networks.

OpenQDC: Open Quantum Data Commons Molecular dynamics simulations with quantum mechanics/molec- ular mechanics and adaptive neural networks

Reference 34

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Observation eba4b91a-80e5-4a95-9364-ad9de055bdb5 · outbound

This paper cites an unresolved cited work.

OpenQDC: Open Quantum Data Commons Unresolved cited work

Reference 35

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Observation 527eaf41-9ab0-4d26-bc4f-539db833a1cb · outbound

This paper cites Learning multiple layers of features from tiny images.

OpenQDC: Open Quantum Data Commons Learning multiple layers of features from tiny images

Reference 36

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Observation 195dd4b4-b9d1-49e5-b89d-66d19f567e34 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

OpenQDC: Open Quantum Data Commons The cityscapes dataset for semantic urban scene understanding

Reference 37

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Observation 38cb714e-bd93-43ac-96c1-ad6c73bdd738 · outbound

This paper cites Pointer sentinel mixture models, 2016.

OpenQDC: Open Quantum Data Commons Pointer sentinel mixture models, 2016

Reference 38

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Observation c44c2f8c-61b8-444e-aa84-a13d2797c804 · outbound

This paper cites CCNet: Extracting high quality monolingual datasets from web crawl data.

OpenQDC: Open Quantum Data Commons CCNet: Extracting high quality monolingual datasets from web crawl data

Reference 39

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Observation f992756a-01ae-42a4-8fff-49cc58ac32a9 · outbound

This paper cites Unsupervised cross-lingual representation learning at scale.

OpenQDC: Open Quantum Data Commons Unsupervised cross-lingual representation learning at scale

Reference 40

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Observation 92d59e94-12d5-4be3-b94c-bec577c0baf5 · outbound

This paper cites Datasets: A community library for natural language processing.

OpenQDC: Open Quantum Data Commons Datasets: A community library for natural language processing

Reference 41

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Observation 744f4739-37cc-4464-b514-ba6ca74df737 · outbound

This paper cites Torchvision: Pytorch’s computer vision library.

OpenQDC: Open Quantum Data Commons Torchvision: Pytorch’s computer vision library

Reference 42

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Observation 9c4953b7-bdef-43d2-ba18-15064f604624 · outbound

This paper cites Therapeutics data commons: Machine learning datasets and tasks for drug discovery and development.

OpenQDC: Open Quantum Data Commons Therapeutics data commons: Machine learning datasets and tasks for drug discovery and development

Reference 43

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source=pdf_text observed=2026-08-12T06:01:04.443990Z digest=sha256:b4c0a15fbebe393548060d845fec0188a18516a3eeec053daa0f298a4f318f67

Observation a972224e-2361-4070-bc67-26c10495c7e3 · outbound

This paper cites an unresolved cited work.

OpenQDC: Open Quantum Data Commons Unresolved cited work

Reference 44

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Observation 89cbdaec-7123-4e6a-93bc-edbfd2dc7838 · outbound

This paper cites The molssi qcarchive project: An open-source platform to compute, organize, and share quantum chemistry data.

OpenQDC: Open Quantum Data Commons The molssi qcarchive project: An open-source platform to compute, organize, and share quantum chemistry data

Reference 45

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source=pdf_text observed=2026-08-12T06:01:04.454489Z digest=sha256:b2af357eca7ae555a18059ed53645b0adde793018b9076c6a1144829bb4dfae6

Observation f56afd72-7e98-49b3-9324-a014559545d0 · outbound

This paper cites Colabfit exchange: Open-access datasets for data-driven interatomic potentials.

OpenQDC: Open Quantum Data Commons Colabfit exchange: Open-access datasets for data-driven interatomic potentials

Reference 46

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source=pdf_text observed=2026-08-12T06:01:04.459709Z digest=sha256:9c5e95ae6dc0b27a92cfe0093e7b0ae07a08b9117094bc093b1209c94971ff2c

Observation 703fc173-9c6a-4298-befc-cfe5965243e0 · outbound

This paper cites Quantum chemical bench- mark energy and geometry database for molecular clusters and complex molecular systems (www.

OpenQDC: Open Quantum Data Commons Quantum chemical bench- mark energy and geometry database for molecular clusters and complex molecular systems (www

Reference 47

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source=pdf_text observed=2026-08-12T06:01:04.464462Z digest=sha256:ecf3bd867e07c97482a50148ae249913619e736d8dd9a64cc62901a42f5c140a

Observation 484eebd2-066a-4e38-b9ee-ce3a5d518432 · outbound

This paper cites Cuby: An integrative framework for computational chemistry, 2016.

OpenQDC: Open Quantum Data Commons Cuby: An integrative framework for computational chemistry, 2016

Reference 48

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source=pdf_text observed=2026-08-12T06:01:04.469539Z digest=sha256:c91b0179b91f298e8ec72149645d73d47a739e020e4514e85e2ae57730880af0

Observation c35ff4d2-ad03-464e-a819-d1d640d9ea0d · outbound

This paper cites Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development.

OpenQDC: Open Quantum Data Commons Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development

Reference 49

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no resolver link, observed 2026-08-12T06:01:04.475284Z

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source=pdf_text observed=2026-08-12T06:01:04.475284Z digest=sha256:9f3ebeb7356cd44fff02c898be5c6b34225844fc697a636ecfb7b382ebcf1adc

Observation 409e5806-f4c5-4498-8b21-3de9dc591461 · outbound

This paper cites Moleculenet: a benchmark for molecular machine learning.

OpenQDC: Open Quantum Data Commons Moleculenet: a benchmark for molecular machine learning

Reference 50

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raw_fallback, observed 2026-08-12T06:01:06.113126Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T06:01:04.480614Z digest=sha256:23f8b9591fdb116992e56ddff755199ae6aa450530d48530d5a4e3ae6e554cee

Observation 2ede94f9-28de-4c9c-bfdb-7435c1673e68 · outbound

This paper cites an unresolved cited work.

OpenQDC: Open Quantum Data Commons Unresolved cited work

Reference 51

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source=pdf_text observed=2026-08-12T06:01:04.485588Z digest=sha256:ba7fab5f28cd1aab19b73e277ca61dfa637987dedca73b8ebe96c5f00573b105

Observation b30d835f-0055-4dee-bfcb-8ed848cb3e2d · outbound

This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.

OpenQDC: Open Quantum Data Commons Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 52

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source=pdf_text observed=2026-08-12T06:01:04.493127Z digest=sha256:87985942f7774d1a380f659dd7a0d6886f85764765588dcbb317f7bc131b741c

Observation d4ae8b1a-59f1-40c4-b439-65c1d17d06c3 · outbound

This paper cites Torchdrug: A powerful and flexible machine learning platform for drug discovery, 2022.

OpenQDC: Open Quantum Data Commons Torchdrug: A powerful and flexible machine learning platform for drug discovery, 2022

Reference 53

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raw_fallback, observed 2026-08-12T06:01:06.084332Z

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source=pdf_text observed=2026-08-12T06:01:04.498992Z digest=sha256:5882fc774faa184596a573c7609e52775680a9005518967d7936a015c86111a7

Observation 43f99f40-9a1d-4c28-aa0d-5265a6f3228a · outbound

This paper cites an unresolved cited work.

OpenQDC: Open Quantum Data Commons Unresolved cited work

Reference 54

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Observation b17b8f8b-9592-4d60-8f54-be59bf3bfee1 · outbound

This paper cites Electronic spectra from tddft and machine learning in chemical space.

OpenQDC: Open Quantum Data Commons Electronic spectra from tddft and machine learning in chemical space

Reference 55

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source=pdf_text observed=2026-08-12T06:01:04.510147Z digest=sha256:cdd170107bc90f2104b62d18b0e15b9b6d0a5f59b6439e2fbd44c59011b7b7ec

Observation 2a7f6bee-0a3f-4cf4-b89b-2c128d0b8303 · outbound

This paper cites Quantum chemistry structures and properties of 134 kilo molecules.

OpenQDC: Open Quantum Data Commons Quantum chemistry structures and properties of 134 kilo molecules

Reference 56

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source=pdf_text observed=2026-08-12T06:01:04.515602Z digest=sha256:997ebfc45b5d5a197e6037c37ec4b9ae82a6c01904091f7ee8c6f48f0766c7ea

Observation 43976007-83c6-44b1-b84f-76d0b93cc36e · outbound

This paper cites Pubchemqc pm6: Data sets of 221 million molecules with optimized molecular geometries and electronic properties.

OpenQDC: Open Quantum Data Commons Pubchemqc pm6: Data sets of 221 million molecules with optimized molecular geometries and electronic properties

Reference 58

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raw_fallback, observed 2026-08-12T06:01:06.002818Z

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Observation 089cacc5-7b14-4911-a091-a5ebd9e6fdb8 · outbound

This paper cites OGB-LSC: A large-scale challenge for machine learning on graphs.

OpenQDC: Open Quantum Data Commons OGB-LSC: A large-scale challenge for machine learning on graphs

Reference 59

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raw_fallback, observed 2026-08-12T06:01:05.981314Z

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source=pdf_text observed=2026-08-12T06:01:04.529736Z digest=sha256:7552072f2737355e5adab28fd778cf89fb60cd2a02c40f5830b1b09225f9ce9f

Observation d9747d2a-0d09-4c7a-9d0d-68dac00735db · outbound

This paper cites Deepmd-kit: A deep learning package for many-body potential energy representation and molecular dynamics.

OpenQDC: Open Quantum Data Commons Deepmd-kit: A deep learning package for many-body potential energy representation and molecular dynamics

Reference 60

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raw_fallback, observed 2026-08-12T06:01:05.964176Z

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Observation 32be80c5-3234-4a3f-8ca1-7e1dde465ca9 · outbound

This paper cites Dp-gen: A concurrent learning platform for the generation of reliable deep learning based potential energy models.

OpenQDC: Open Quantum Data Commons Dp-gen: A concurrent learning platform for the generation of reliable deep learning based potential energy models

Reference 61

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Observation 40fb02a7-272b-435f-9cd5-b00b11be62de · outbound

This paper cites Pinn: A python library for building atomic neural networks of molecules and materials.

OpenQDC: Open Quantum Data Commons Pinn: A python library for building atomic neural networks of molecules and materials

Reference 62

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Observation ede7ddd5-3cae-46ff-816d-96b3ef97a458 · outbound

This paper cites Elliott, and Ellad B.

OpenQDC: Open Quantum Data Commons Elliott, and Ellad B

Reference 63

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source=pdf_text observed=2026-08-12T06:01:04.552430Z digest=sha256:ca17050ce31f1619559ea44fd991fbf2513a2350605831436ca37dc558c2e778

Observation 38e9f85d-1e23-4e4d-a021-6b78f8c0265a · outbound

This paper cites Jax md: a framework for differentiable physics.

OpenQDC: Open Quantum Data Commons Jax md: a framework for differentiable physics

Reference 64

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0ad07671-2a83-467a-ad48-50df1b72528c · outbound

This paper cites Torchmd: A deep learning framework for molecular simulations.

OpenQDC: Open Quantum Data Commons Torchmd: A deep learning framework for molecular simulations

Reference 65

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Observation 9d3d4ebb-f181-460d-be1c-b63b8ddea26f · outbound

This paper cites Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E.

OpenQDC: Open Quantum Data Commons Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E

Reference 66

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source=pdf_text observed=2026-08-12T06:01:04.567618Z digest=sha256:de4543a19015b5cb7215e28a076f8cb13eeecf6da876573b7c400cbb07c4930a

Observation 48322f36-0ca9-4522-bd11-01287640a934 · outbound

This paper cites Tensornet: Cartesian tensor representations for efficient learning of molecular potentials.

OpenQDC: Open Quantum Data Commons Tensornet: Cartesian tensor representations for efficient learning of molecular potentials

Reference 67

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raw_fallback, observed 2026-08-12T06:01:05.867035Z

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Observation fb3ad61b-13fc-4e57-adb8-c4f169e606a9 · outbound

This paper cites Charron, Toni Giorgino, Brooke E.

OpenQDC: Open Quantum Data Commons Charron, Toni Giorgino, Brooke E

Reference 68

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source=pdf_text observed=2026-08-12T06:01:04.580053Z digest=sha256:7e57215d558066d4aa185054868825dce14a72a1cc462d8096a3689c76743ae8

Observation 93a5baa3-ad6b-4082-9289-6a900a4733eb · outbound

This paper cites Quantum-chemical insights from deep tensor neural networks.

OpenQDC: Open Quantum Data Commons Quantum-chemical insights from deep tensor neural networks

Reference 69

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ca956f13-d98b-4fc9-b76f-f8f0d06bcbd7 · outbound

This paper cites Schnet–a deep learning architecture for molecules and materials.

OpenQDC: Open Quantum Data Commons Schnet–a deep learning architecture for molecules and materials

Reference 71

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raw_fallback, observed 2026-08-12T06:01:05.824034Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f6e8ac4d-e824-49a8-a54a-17224bc0151f · outbound

This paper cites Schnetpack: A deep learning toolbox for atomistic systems.

OpenQDC: Open Quantum Data Commons Schnetpack: A deep learning toolbox for atomistic systems

Reference 72

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0effbccb-270c-46ed-9db8-303e465d0332 · outbound

This paper cites Thermal half-lives of azobenzene derivatives: Virtual screening based on intersystem crossing using a machine learning potential.

OpenQDC: Open Quantum Data Commons Thermal half-lives of azobenzene derivatives: Virtual screening based on intersystem crossing using a machine learning potential

Reference 73

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 725de08d-9822-479f-b729-ed5e38fbb0e7 · outbound

This paper cites Excited state non- adiabatic dynamics of large photoswitchable molecules using a chemically transferable ma- chine learning potential.

OpenQDC: Open Quantum Data Commons Excited state non- adiabatic dynamics of large photoswitchable molecules using a chemically transferable ma- chine learning potential

Reference 74

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raw_fallback, observed 2026-08-12T06:01:05.772480Z

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source=pdf_text observed=2026-08-12T06:01:04.612064Z digest=sha256:3e3b42a42eefdc16324f3e4b6f3d8a8b99121ea73672a63d9dfc9f96c6cc1d91

Observation 86d0bec5-9274-401d-a2a7-8fcfc22fd449 · outbound

This paper cites Mace: Higher order equivariant message passing neural networks for fast and accurate force fields.

OpenQDC: Open Quantum Data Commons Mace: Higher order equivariant message passing neural networks for fast and accurate force fields

Reference 75

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Source-reported events for the cited work

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Observation 5381602b-8d66-4923-94b0-4e943017abcb · outbound

This paper cites The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.

OpenQDC: Open Quantum Data Commons The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 76

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source=pdf_text observed=2026-08-12T06:01:04.621569Z digest=sha256:3e3e67b513c87adc175be90b0738e310ea717adaa6bddebaf593899cd2207845

Observation 80777ac1-7804-4238-a075-42f1edd8afc1 · outbound

This paper cites A foundation model for atomistic materials chemistry.

OpenQDC: Open Quantum Data Commons A foundation model for atomistic materials chemistry

Reference 77

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source=pdf_text observed=2026-08-12T06:01:04.626433Z digest=sha256:053938bae8cc11ed67af7f881b38ac54074faf1f131ffb5688ad6ba6604d5332

Observation 3a4b599c-99aa-48aa-82ea-2b55f38aca8c · outbound

This paper cites e3nn: Euclidean Neural Networks.

OpenQDC: Open Quantum Data Commons e3nn: Euclidean Neural Networks

Reference 78

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f989eaa-9623-42d7-bbea-08c34d7c478b · outbound

This paper cites an unresolved cited work.

OpenQDC: Open Quantum Data Commons Unresolved cited work

Reference 79

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f2d78aac-5211-4a4f-af6d-a203e020dcc1 · outbound

This paper cites Less is more: Sampling chemical space with active learning.

OpenQDC: Open Quantum Data Commons Less is more: Sampling chemical space with active learning

Reference 80

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raw_fallback, observed 2026-08-12T06:01:05.726284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 671f2a1a-88d0-4a67-aba4-09380469bfe5 · outbound

This paper cites The ani-1ccx and ani-1x data sets, coupled-cluster and density functional theory properties for molecules.

OpenQDC: Open Quantum Data Commons The ani-1ccx and ani-1x data sets, coupled-cluster and density functional theory properties for molecules

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-12T06:01:05.708406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation bd850824-d677-46d5-932e-2a25382dd028 · outbound

This paper cites Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.

OpenQDC: Open Quantum Data Commons Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

Reference 82

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raw_fallback, observed 2026-08-12T06:01:05.690558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 53eb722b-26a1-4aee-a7a1-6d68927f3ad0 · outbound

This paper cites Chembl: towards direct deposition of bioassay data.

OpenQDC: Open Quantum Data Commons Chembl: towards direct deposition of bioassay data

Reference 83

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 22b0c466-4c6c-4f8d-8727-d807db764d50 · outbound

This paper cites The s66x8 benchmark for noncovalent interactions revisited: explicitly correlated ab initio methods and density functional theory.

OpenQDC: Open Quantum Data Commons The s66x8 benchmark for noncovalent interactions revisited: explicitly correlated ab initio methods and density functional theory

Reference 84

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raw_fallback, observed 2026-08-12T06:01:05.654389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T06:01:04.661669Z digest=sha256:7de76dfd023cea80df1e84f916577fd382eec444cb0e0273667d518375621f76

Observation 9a8e6dc3-7753-42c6-b002-3f0d023b0f67 · outbound

This paper cites Geom, energy-annotated molecular conforma- tions for property prediction and molecular generation.

OpenQDC: Open Quantum Data Commons Geom, energy-annotated molecular conforma- tions for property prediction and molecular generation

Reference 85

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation cc7ba2dd-ed1b-4669-b94d-d82e43868d15 · outbound

This paper cites Gfn2-xtb—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions.

OpenQDC: Open Quantum Data Commons Gfn2-xtb—an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions

Reference 86

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 26885a43-0c0b-4b6b-8c21-2d273b6afa7a · outbound

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

OpenQDC: Open Quantum Data Commons Schnet: A continuous-filter convolutional neural network for modeling quantum interactions

Reference 87

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unresolved
no resolver link, observed 2026-08-12T06:01:04.675743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T06:01:04.675743Z digest=sha256:fc9a375ae5c965bf632eefcb2b1c877397cd9937bf27bd0f0d0e41c230a08183

Observation d1cea826-bd80-4075-9afc-3c2a32177239 · outbound

This paper cites Accurate global machine learning force fields for molecules with hundreds of atoms.

OpenQDC: Open Quantum Data Commons Accurate global machine learning force fields for molecules with hundreds of atoms

Reference 88

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raw_fallback, observed 2026-08-12T06:01:05.603842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 05c1b4ed-9e4c-4df2-9869-34711c1895e8 · outbound

This paper cites Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs.

OpenQDC: Open Quantum Data Commons Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs

Reference 89

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no resolver link, observed 2026-08-12T06:01:04.685219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a1ee21db-bbe4-4bba-bd3f-ac9aeb35b5d4 · outbound

This paper cites Multixc-qm9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods.

OpenQDC: Open Quantum Data Commons Multixc-qm9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods

Reference 90

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T06:01:04.690769Z digest=sha256:6e8f734a539df0fd873b3f24b33bbd43c4e58d8bb70f27988f23862c1d82027b

Observation 77b49cd2-eeaf-4490-bc54-1968327adeff · outbound

This paper cites Quantum chemistry structures and properties of 134 kilo molecules.

OpenQDC: Open Quantum Data Commons Quantum chemistry structures and properties of 134 kilo molecules

Reference 91

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raw_fallback, observed 2026-08-12T06:01:05.575486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d3954375-91b3-4382-8284-f06c4cfed92f · outbound

This paper cites nabladft: Large-scale conformational energy and hamiltonian prediction benchmark and dataset.

OpenQDC: Open Quantum Data Commons nabladft: Large-scale conformational energy and hamiltonian prediction benchmark and dataset

Reference 92

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raw_fallback, observed 2026-08-12T06:01:05.558173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3b446486-07e0-4a87-9cbd-81d95abd1544 · outbound

This paper cites Orbnet denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and dft accuracy.

OpenQDC: Open Quantum Data Commons Orbnet denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and dft accuracy

Reference 93

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T06:01:04.706408Z digest=sha256:be7d1f35a7ab8b1e8c1648b875f09a7a94e4349fc0420de4eb7ab2a24aac82b2

Observation 80d9a8f3-da00-42d9-a9d9-9af795b36c83 · outbound

This paper cites Pubchem 2023 update.

OpenQDC: Open Quantum Data Commons Pubchem 2023 update

Reference 94

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no resolver link, observed 2026-08-12T06:01:04.711501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T06:01:04.711501Z digest=sha256:a3cb8d24ece3dc1ce52063d92b045329db80700d6d612f7d4cece43e18f24b63

Observation ba095047-decc-4ee2-b302-df78197b39d5 · outbound

This paper cites Pubchemqc b3lyp/6-31g*//pm6 data set: The electronic structures of 86 million molecules using b3lyp/6-31g* calculations.

OpenQDC: Open Quantum Data Commons Pubchemqc b3lyp/6-31g*//pm6 data set: The electronic structures of 86 million molecules using b3lyp/6-31g* calculations

Reference 95

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no resolver link, observed 2026-08-12T06:01:04.716305Z

Source-reported events for the cited work

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Observation f34c2d03-e923-4740-8b38-9119d9829707 · outbound

This paper cites Qm7-x, a comprehensive dataset of quantum- mechanical properties spanning the chemical space of small organic molecules.

OpenQDC: Open Quantum Data Commons Qm7-x, a comprehensive dataset of quantum- mechanical properties spanning the chemical space of small organic molecules

Reference 96

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raw_fallback, observed 2026-08-12T06:01:05.504200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a77a7831-8468-4792-9f9a-10e065f2e6b2 · outbound

This paper cites Qmugs, quantum mechanical properties of drug-like molecules.

OpenQDC: Open Quantum Data Commons Qmugs, quantum mechanical properties of drug-like molecules

Reference 97

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raw_fallback, observed 2026-08-12T06:01:05.487553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 25ce238d-ea41-4628-9bc7-edc2f1383fae · outbound

This paper cites On the role of gradients for machine learning of molecular energies and forces.

OpenQDC: Open Quantum Data Commons On the role of gradients for machine learning of molecular energies and forces

Reference 98

Resolution
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raw_fallback, observed 2026-08-12T06:01:05.470641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b0e45125-169c-4771-bd83-dd9adff58b37 · outbound

This paper cites Machine learning of accurate energy-conserving molecular force fields.

OpenQDC: Open Quantum Data Commons Machine learning of accurate energy-conserving molecular force fields

Reference 99

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raw_fallback, observed 2026-08-12T06:01:06.021783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T06:01:04.735083Z digest=sha256:5d2213243ecbc919667ca429c1de12aec96998047aeeb1618115deaa60a62f93

Observation 5ae98d5d-e360-46e1-9ee7-b97bcc3a9c87 · outbound

This paper cites Physnet: A neural network for predicting energies, forces, dipole moments, and partial charges.

OpenQDC: Open Quantum Data Commons Physnet: A neural network for predicting energies, forces, dipole moments, and partial charges

Reference 100

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raw_fallback, observed 2026-08-12T06:01:05.454583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T06:01:04.739761Z digest=sha256:1d2df418ddfcd1498fe35319b4e981c1791950a5ada128430ac5a19d6239fb9b

Observation 938880c7-fa08-4961-8d55-ee11bd1cefb6 · outbound

This paper cites Spice, a dataset of drug-like molecules and peptides for training machine learning potentials.

OpenQDC: Open Quantum Data Commons Spice, a dataset of drug-like molecules and peptides for training machine learning potentials

Reference 101

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raw_fallback, observed 2026-08-12T06:01:05.438350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T06:01:04.745534Z digest=sha256:b52ba5c8e91bbd017f24f4a6e37af3f6880f0af5c21797b2a3f705cd1b2f9b2e

Observation 323ddd80-1237-4dfb-a433-4bd004560add · outbound

This paper cites Spice 2.0.1, April 2024.

OpenQDC: Open Quantum Data Commons Spice 2.0.1, April 2024

Reference 102

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no resolver link, observed 2026-08-12T06:01:04.750870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T06:01:04.750870Z digest=sha256:cd7ca341581df3047ecfc7ebe4ba0411f446cef6b9eabf47ce8ae4860943eaec

Pith citing papers

No inbound Pith citation observations are available.