Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T16:10:54.353010Z
Paper Citation Record · LEDGER
DEQuify your force field: More efficient simulations using deep equilibrium models
As of 18 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2509.08734.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
49 of 49 outbound references displayed
- verified exact0
- verified fuzzy39
- unresolved9
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b58a94bc-826e-4c90-b76d-6d197ebc04c7 · outbound
This paper cites Cormorant: Covariant molecular neural networks.Advances in neural information processing systems, 32, 2019.
DEQuify your force field: More efficient simulations using deep equilibrium models Cormorant: Covariant molecular neural networks.Advances in neural information processing systems, 32, 2019
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.969891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation eb7aca99-7f21-4e3c-8b61-139ca44711c1 · outbound
This paper cites Anderson.
DEQuify your force field: More efficient simulations using deep equilibrium models Anderson
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.959400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 09d61869-0395-4da5-a2c2-959abef641b3 · outbound
This paper cites Zico Kolter.
DEQuify your force field: More efficient simulations using deep equilibrium models Zico Kolter
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.949717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5f2de210-21c0-4f4a-9882-b89a51b28008 · outbound
This paper cites Trellis Networks for Sequence Modeling.
DEQuify your force field: More efficient simulations using deep equilibrium models Trellis Networks for Sequence Modeling
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.173238Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dead9b8-5cfb-41f9-9c95-77a30e2834a6 · outbound
This paper cites Zico Kolter, and Vladlen Koltun.
DEQuify your force field: More efficient simulations using deep equilibrium models Zico Kolter, and Vladlen Koltun
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.939898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ca2f3640-06e2-4229-ad8d-0c225365d735 · outbound
This paper cites Stabilizing Equilibrium Models by Jacobian Regularization.
DEQuify your force field: More efficient simulations using deep equilibrium models Stabilizing Equilibrium Models by Jacobian Regularization
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.930458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0d87079b-f61a-416b-9998-1d99e416a5ed · outbound
This paper cites Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons.Physical review letters, 104(13):136403, 2010.
DEQuify your force field: More efficient simulations using deep equilibrium models Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons.Physical review letters, 104(13):136403, 2010
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.919905Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c6e71742-b8d1-44ba-8d05-cf3fb84f44e2 · outbound
This paper cites Kovacs, Gregor Simm, Christoph Ortner, and Gabor Csanyi.
DEQuify your force field: More efficient simulations using deep equilibrium models Kovacs, Gregor Simm, Christoph Ortner, and Gabor Csanyi
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.909837Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 23c2640c-f40d-4b5a-9fc8-3819e76ab0cc · outbound
This paper cites Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E.
DEQuify your force field: More efficient simulations using deep equilibrium models Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.900010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 87dcb8e9-6e0d-46eb-97fa-cc6e23d3df7d · outbound
This paper cites Generalized neural-network representation of high- dimensional potential-energy surfaces.Physical review letters, 98(14):146401, 2007.
DEQuify your force field: More efficient simulations using deep equilibrium models Generalized neural-network representation of high- dimensional potential-energy surfaces.Physical review letters, 98(14):146401, 2007
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.889707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0759b5e4-c022-4440-9eb7-5f10a217d4a7 · outbound
This paper cites How Attentive are Graph Attention Networks?.
DEQuify your force field: More efficient simulations using deep equilibrium models How Attentive are Graph Attention Networks?
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.208224Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59b77ea0-071f-42d2-91df-b4327d9b7ffe · outbound
This paper cites an unresolved cited work.
DEQuify your force field: More efficient simulations using deep equilibrium models Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T16:10:54.879985Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7c989e43-d241-4c82-837d-8a0b22b66371 · outbound
This paper cites Deep equilibrium diffusion restoration with parallel sampling.
DEQuify your force field: More efficient simulations using deep equilibrium models Deep equilibrium diffusion restoration with parallel sampling
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.870118Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 17281f2e-8dbb-416b-90cd-2a7f4e395ac3 · outbound
This paper cites Unified approach for molecular dynamics and density- functional theory.Physical review letters, 55(22):2471, 1985.
DEQuify your force field: More efficient simulations using deep equilibrium models Unified approach for molecular dynamics and density- functional theory.Physical review letters, 55(22):2471, 1985
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.859510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e9a2ec5e-5f30-4d67-986d-4240ad48cbbb · outbound
This paper cites Unke, Adil Kabylda, Huziel E.
DEQuify your force field: More efficient simulations using deep equilibrium models Unke, Adil Kabylda, Huziel E
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.848657Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 477df0f0-1b12-40b5-be40-9767ecbae4af · outbound
This paper cites Bartel, and Gerbrand Ceder.
DEQuify your force field: More efficient simulations using deep equilibrium models Bartel, and Gerbrand Ceder
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.838119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation be7e2e1d-9317-4a94-bed2-9bcf65b1ffcd · outbound
This paper cites Molecular dynamics simulations and drug discovery.BMC biology, 9:1–9, 2011.
DEQuify your force field: More efficient simulations using deep equilibrium models Molecular dynamics simulations and drug discovery.BMC biology, 9:1–9, 2011
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.827954Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ca1f4ba9-d121-47be-8e75-fe775069551e · outbound
This paper cites Jfb: Jacobian-free backpropagation for implicit networks.
DEQuify your force field: More efficient simulations using deep equilibrium models Jfb: Jacobian-free backpropagation for implicit networks
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.818078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ebc8535a-77d4-4b19-b316-76b2355aff66 · outbound
This paper cites A theoretically grounded application of dropout in recurrent neural networks.
DEQuify your force field: More efficient simulations using deep equilibrium models A theoretically grounded application of dropout in recurrent neural networks
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.807119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b7c4b734-6218-4426-8c65-3046460f1961 · outbound
This paper cites GemNet: Universal Directional Graph Neural Networks for Molecules.
DEQuify your force field: More efficient simulations using deep equilibrium models GemNet: Universal Directional Graph Neural Networks for Molecules
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.795564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 941c1e23-8ad9-4fbc-9927-309ba0e75e33 · outbound
This paper cites Directional Message Passing for Molecular Graphs.
DEQuify your force field: More efficient simulations using deep equilibrium models Directional Message Passing for Molecular Graphs
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.248150Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed01473a-6482-4e04-ae72-6adf9b93e364 · outbound
This paper cites Zico Kolter.
DEQuify your force field: More efficient simulations using deep equilibrium models Zico Kolter
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.786241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4b4beb25-d987-4412-80ec-c7d72f9436c5 · outbound
This paper cites One-step diffusion distillation via deep equilibrium models.
DEQuify your force field: More efficient simulations using deep equilibrium models One-step diffusion distillation via deep equilibrium models
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.775960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b9b34d1e-4106-489f-8b6d-877ae5c18cb6 · outbound
This paper cites On training implicit models.Advances in Neural Information Processing Systems, 34:24247–24260, 2021.
DEQuify your force field: More efficient simulations using deep equilibrium models On training implicit models.Advances in Neural Information Processing Systems, 34:24247–24260, 2021
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.764680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0c2f1488-b8ca-429a-bb2f-0eb58896808e · outbound
This paper cites Molecular dynamics simulation for all.Neuron, 99(6):1129–1143, 2018.
DEQuify your force field: More efficient simulations using deep equilibrium models Molecular dynamics simulation for all.Neuron, 99(6):1129–1143, 2018
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.752181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 66f0b592-7978-42db-a668-76eecd2d2c19 · outbound
This paper cites Finkler, Stefan Goedecker, and Jörg Behler.
DEQuify your force field: More efficient simulations using deep equilibrium models Finkler, Stefan Goedecker, and Jörg Behler
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.740962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f0d1ba4e-d865-47a0-a19a-3aac448ba199 · outbound
This paper cites Time-reversible always stable predictor–corrector method for molecular dynamics of polarizable molecules.Journal of computational chemistry, 25(3):335–342, 2004.
DEQuify your force field: More efficient simulations using deep equilibrium models Time-reversible always stable predictor–corrector method for molecular dynamics of polarizable molecules.Journal of computational chemistry, 25(3):335–342, 2004
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.730646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 14744974-ee03-402e-b2f9-56405d992e20 · outbound
This paper cites Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation.
DEQuify your force field: More efficient simulations using deep equilibrium models Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.274330Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00e5fa5b-3f8d-4175-a915-d715c062f44b · outbound
This paper cites Long-short-range message-passing: A physics-informed framework to capture non-local interaction for scalable molecular dynamics simulation, 2024.
DEQuify your force field: More efficient simulations using deep equilibrium models Long-short-range message-passing: A physics-informed framework to capture non-local interaction for scalable molecular dynamics simulation, 2024
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.720026Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 11a8979f-125c-4445-a6de-eba5874a664d · outbound
This paper cites Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs, February 2023.
DEQuify your force field: More efficient simulations using deep equilibrium models Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs, February 2023
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.710449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ab4ca0f0-fe4c-4483-b17e-7541c9821ca8 · outbound
This paper cites EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations, March 2024.
DEQuify your force field: More efficient simulations using deep equilibrium models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations, March 2024
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.700043Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1ae1197a-df55-4312-9365-d2992f8d77e1 · outbound
This paper cites Force fields for small molecules.Biomolecular simulations: Methods and protocols, pages 21–54, 2019.
DEQuify your force field: More efficient simulations using deep equilibrium models Force fields for small molecules.Biomolecular simulations: Methods and protocols, pages 21–54, 2019
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.689734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 61337885-b28b-4c0c-b42e-d9e9dc939ff5 · outbound
This paper cites Spherical message passing for 3d molecular graphs.
DEQuify your force field: More efficient simulations using deep equilibrium models Spherical message passing for 3d molecular graphs
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.677783Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 49c97a6a-1f4d-4bf5-b01d-ff02c4df3985 · outbound
This paper cites Owen, Mordechai Kornbluth, and Boris Kozinsky.
DEQuify your force field: More efficient simulations using deep equilibrium models Owen, Mordechai Kornbluth, and Boris Kozinsky
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.667645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 28f9bd80-4e06-4c12-9841-1a032b613f93 · outbound
This paper cites Lawrence Zitnick.
DEQuify your force field: More efficient simulations using deep equilibrium models Lawrence Zitnick
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.655517Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation bed68e2b-9dff-4085-ab4c-f78c7893a011 · outbound
This paper cites an unresolved cited work.
DEQuify your force field: More efficient simulations using deep equilibrium models Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T16:10:54.644417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a66acf4e-d2e9-4b68-b674-bac426566be6 · outbound
This paper cites Schnet: A continuous-filter convolutional neural network for modeling quantum interactions.Advances in neural information processing systems, 30,.
DEQuify your force field: More efficient simulations using deep equilibrium models Schnet: A continuous-filter convolutional neural network for modeling quantum interactions.Advances in neural information processing systems, 30,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.632096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 64cc34da-1f65-46c2-9f4a-d381ecde24ab · outbound
This paper cites Equivariant message passing for the prediction of tensorial properties and molecular spectra.
DEQuify your force field: More efficient simulations using deep equilibrium models Equivariant message passing for the prediction of tensorial properties and molecular spectra
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.621285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cfa8a7bb-95a3-4cf0-aee2-3e8a1cee47d8 · outbound
This paper cites Moment tensor potentials: A class of systematically improvable inter- atomic potentials.Multiscale Modeling & Simulation, 14(3):1153–1173, 2016.
DEQuify your force field: More efficient simulations using deep equilibrium models Moment tensor potentials: A class of systematically improvable inter- atomic potentials.Multiscale Modeling & Simulation, 14(3):1153–1173, 2016
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.610600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ab84eb29-196e-4864-a33d-95c84b1bcac7 · outbound
This paper cites From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction.
DEQuify your force field: More efficient simulations using deep equilibrium models From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.317763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b5a784d-c418-411b-9436-53187ff96fc2 · outbound
This paper cites Applications of molecular dynamics simulation in protein study.Membranes, 12(9):844, 2022.
DEQuify your force field: More efficient simulations using deep equilibrium models Applications of molecular dynamics simulation in protein study.Membranes, 12(9):844, 2022
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.599787Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 52a39751-9b56-4309-b75a-46cff4c20b09 · outbound
This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.
DEQuify your force field: More efficient simulations using deep equilibrium models Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.324871Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2deb18e1-8c81-4420-aa9f-debe4e1985f7 · outbound
This paper cites Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials.Journal of Computational Physics, 285:316–330, 2015.
DEQuify your force field: More efficient simulations using deep equilibrium models Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials.Journal of Computational Physics, 285:316–330, 2015
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.587338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a58fe5b0-230d-4c5f-a5e4-bd96363e9634 · outbound
This paper cites ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules.
DEQuify your force field: More efficient simulations using deep equilibrium models ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:10:54.334117Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f013dd1-2224-4f2b-b9a5-5e73d1dab777 · outbound
This paper cites Efficiently incorporating quintuple interactions into geometric deep learning force fields.Advances in Neural Information Processing Systems, 36, 2024.
DEQuify your force field: More efficient simulations using deep equilibrium models Efficiently incorporating quintuple interactions into geometric deep learning force fields.Advances in Neural Information Processing Systems, 36, 2024
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.573820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9b7c4932-6a0e-48c1-b1f4-edd26b92d467 · outbound
This paper cites Amber: Assisted model building with energy refinement.
DEQuify your force field: More efficient simulations using deep equilibrium models Amber: Assisted model building with energy refinement
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.562633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4032ccbd-7dcd-403d-8aa0-6260ed486652 · outbound
This paper cites Lightweight equivariant model for efficient machine learning interatomic potentials, 2024.
DEQuify your force field: More efficient simulations using deep equilibrium models Lightweight equivariant model for efficient machine learning interatomic potentials, 2024
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.550469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6d1ada3f-4ea9-45f0-815f-d2394c84863a · outbound
This paper cites Limitations.
DEQuify your force field: More efficient simulations using deep equilibrium models Limitations
Reference 48
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-15T16:10:54.448546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e4a02d9f-c151-49ba-b8cc-f4862ff4dbbf · outbound
This paper cites • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research.
DEQuify your force field: More efficient simulations using deep equilibrium models • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T16:10:54.537044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.