MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields | Paper Citation Record

Observation d4bcce68-0cf7-4a43-8aa2-33a86b47c66a · inbound

Effects of Four-Phonon Scattering and Wave-like Phonon Tunneling Effects on Thermoelectric Properties of Mg2GeSe4 using Machine Learning cites this paper.

Effects of Four-Phonon Scattering and Wave-like Phonon Tunneling Effects on Thermoelectric Properties of Mg2GeSe4 using Machine Learning MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T19:37:29.061923Z

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Observation 6e9f0638-c0fd-4c37-b78c-d35141f5ed76 · inbound

Neural Network Potential with Multi-Resolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution cites this paper.

Neural Network Potential with Multi-Resolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T06:01:01.039115Z

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Observation 8d5dbdb0-280c-4e47-a9e9-2055c3914b3f · inbound

BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps cites this paper.

BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:25.169346Z

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Observation 9db51e7b-a41e-41e0-bbe8-3005abf29d21 · inbound

Application of pretrained universal machine-learning interatomic potential for physicochemical simulation of liquid electrolytes in Li-ion battery cites this paper.

Application of pretrained universal machine-learning interatomic potential for physicochemical simulation of liquid electrolytes in Li-ion battery MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 2453

Resolution: unresolved; no resolver link, observed 2026-08-10T21:17:21.145388Z

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Observation a434fcc6-2f49-4d7d-beed-117040b85804 · inbound

Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration cites this paper.

Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T21:05:47.491558Z

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Observation 4a48d2a2-71a0-4a4d-95e6-1f082e59bcc9 · inbound

Uncertainty Quantification for Misspecified Machine Learned Interatomic Potentials cites this paper.

Uncertainty Quantification for Misspecified Machine Learned Interatomic Potentials MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-08T13:51:43.320927Z

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Unavailable: canonical work link unavailable.

Observation 9546551a-93ed-4e72-8a0f-19fa4e702f97 · inbound

Iterative charge equilibration for fourth-generation high-dimensional neural network potentials cites this paper.

Iterative charge equilibration for fourth-generation high-dimensional neural network potentials MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T11:30:49.351340Z

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Observation 44481325-3a91-4302-826f-4a92b21c4f15 · inbound

Full-cycle device-scale simulations of memory materials with a tailored atomic-cluster-expansion potential cites this paper.

Full-cycle device-scale simulations of memory materials with a tailored atomic-cluster-expansion potential MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T05:20:25.437243Z

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Observation 54335129-ab51-4059-b618-a856bfc40a84 · inbound

Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors cites this paper.

Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T19:56:13.109617Z

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Unavailable: canonical work link unavailable.

Observation 8e113dbe-5787-40c5-98f7-b506a47f0e13 · inbound

System of Agentic AI for the Discovery of Metal-Organic Frameworks cites this paper.

System of Agentic AI for the Discovery of Metal-Organic Frameworks MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T12:03:09.196490Z

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Observation 394d147a-d2cc-4025-975b-5e85562ad5f9 · inbound

AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use cites this paper.

AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T20:34:12.833801Z

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Observation d9d4f1ca-4a08-4f0d-94c2-abf016346084 · inbound

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems cites this paper.

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T13:13:22.736105Z

Source-reported events for the cited work

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Observation 0fa232d0-f315-4f56-8d28-b0d6f6e027a5 · inbound

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations cites this paper.

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T10:55:21.511203Z

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Observation 6ae8b7e7-c87b-43ab-8153-e38491825fb6 · inbound

ChemGraph: An Agentic Framework for Computational Chemistry Workflows cites this paper.

ChemGraph: An Agentic Framework for Computational Chemistry Workflows MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T11:07:08.757116Z

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Observation ba5771e2-8e20-4ebf-b5e3-47e78280af8c · inbound

Comparing classical and machine learning force fields for modeling deformation of solid sorbents relevant for direct air capture cites this paper.

Comparing classical and machine learning force fields for modeling deformation of solid sorbents relevant for direct air capture MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:40.253749Z

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Observation 0b922a01-684f-469f-bcef-55fc7fb8091d · inbound

Distillation of atomistic foundation models across architectures and chemical domains cites this paper.

Distillation of atomistic foundation models across architectures and chemical domains MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T04:17:21.987291Z

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Observation 0858ca8d-bedb-4e8c-8d64-87943163dcb8 · inbound

An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials cites this paper.

An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T19:44:50.392157Z

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Observation b6d10057-c465-4fbb-b437-de897915f5f9 · inbound

Reducing Self-Interaction Error in Transition-Metal Oxides with Different Exact-Exchange Fractions for Energy and Density cites this paper.

Reducing Self-Interaction Error in Transition-Metal Oxides with Different Exact-Exchange Fractions for Energy and Density MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T07:42:59.924574Z

Source-reported events for the cited work

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

Observation 66930914-0dfb-478e-87ee-9f5af4d5f0f4 · inbound

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy cites this paper.

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:25:45.261233Z

Source-reported events for the cited work

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

Observation abd0d89d-9351-4f59-bbe8-3fb6511e8b2c · inbound

MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling cites this paper.

MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T17:07:38.062526Z

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Observation 0d3039a4-0e2a-4218-8f75-ecf4141ade76 · inbound

Dis-GEN: Disordered crystal structure generation cites this paper.

Dis-GEN: Disordered crystal structure generation MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T18:21:42.183951Z

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Observation 478f872b-d90e-4bc7-b39f-ba8e6cba228c · inbound

Clay Edges Are Dynamic Proton-conducting Networks Modulated by Structure and pH cites this paper.

Clay Edges Are Dynamic Proton-conducting Networks Modulated by Structure and pH MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T17:59:34.369367Z

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Observation f70d0aa5-de02-48c4-af20-3c2899c613bf · inbound

Universal Machine Learning Potential for Systems with Reduced Dimensionality cites this paper.

Universal Machine Learning Potential for Systems with Reduced Dimensionality MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T17:53:48.986707Z

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Observation eed59ce7-6692-4afb-b04b-bf0b96e04bb3 · inbound

Universal Machine Learning Potentials under Pressure cites this paper.

Universal Machine Learning Potentials under Pressure MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T16:48:25.035057Z

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Observation 5d6a1b31-76bc-406e-b018-004cc9a019fb · inbound

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework cites this paper.

Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T05:52:52.865241Z

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Observation e7b8016d-adcc-4835-8543-6b2113f5060c · inbound

Towards Accurate and Scalable High-throughput MOF Adsorption Screening: Merging Classical Force Fields and Universal Machine Learned Interatomic Potentials cites this paper.

Towards Accurate and Scalable High-throughput MOF Adsorption Screening: Merging Classical Force Fields and Universal Machine Learned Interatomic Potentials MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T23:16:05.778525Z

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Observation 128d19bf-7d86-4622-a394-a8b91a2b8ba6 · inbound

Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations cites this paper.

Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T15:57:14.775254Z

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Observation 1132a82f-ceb0-4140-8845-28f40384f910 · inbound

Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing cites this paper.

Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T10:02:31.558400Z

Source-reported events for the cited work

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

Observation 199222a0-c0c3-4755-88d8-1bdc003047f2 · inbound

Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries cites this paper.

Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T09:21:09.842064Z

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

Observation 0216a9bc-4976-4c5c-9227-0ab98f456d5b · inbound

Benchmarking foundation potentials against quantum chemistry methods for predicting molecular redox potentials cites this paper.

Benchmarking foundation potentials against quantum chemistry methods for predicting molecular redox potentials MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T07:54:29.274141Z

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Observation 4ea4aa5a-0300-4a5c-a881-53ca9eee083d · inbound

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model cites this paper.

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 579

Resolution: unresolved; no resolver link, observed 2026-08-03T11:46:14.483234Z

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Observation fe0f146d-e1bc-4a82-844a-10cb9151a526 · inbound

QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities cites this paper.

QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:50:49.264023Z

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

Observation 5dd6a8ed-0902-40ec-b162-396285a245db · inbound

Electron dynamics mediate the water-carbon {\pi} bond cites this paper.

Electron dynamics mediate the water-carbon {\pi} bond MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:23:05.794124Z

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

Observation c5023a33-ca80-4dcb-bfd4-e4763ead2ec7 · inbound

Force Field-Agnostic Phase Classification of Zeolitic Imidazolate Framework Polymorphs cites this paper.

Force Field-Agnostic Phase Classification of Zeolitic Imidazolate Framework Polymorphs MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:10:58.189347Z

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

Observation 6732af87-d672-434d-9948-2337cd7af70e · inbound

Accelerating point defect simulations using data-driven and machine learning approaches cites this paper.

Accelerating point defect simulations using data-driven and machine learning approaches MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 92

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:06:05.167427Z

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

Observation dae3c7e8-9511-491b-be4c-33a6ed6cfe91 · inbound

Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS cites this paper.

Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:56:07.457705Z

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

Observation 48aa33e5-3648-40d5-95c9-fc71369941e1 · inbound

Data-Driven Thermal and Mechanical Modeling of Defective Covalent Organic Frameworks cites this paper.

Data-Driven Thermal and Mechanical Modeling of Defective Covalent Organic Frameworks MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-09T21:08:22.664312Z

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

Observation cd4aab05-e017-4337-9800-3f568602271d · inbound

DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory cites this paper.

DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:09.137347Z

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

Observation 0db19ba0-f42d-4cd8-977a-abd29c8255f5 · inbound

DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory cites this paper.

DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:26:29.389431Z

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

Observation 98bb25a1-a3c3-4998-9513-66f90e41c21d · inbound

DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory cites this paper.

DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-02T15:39:39.073658Z

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Observation 65a786e7-d226-4475-93c1-40576ad39d94 · inbound

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement cites this paper.

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T10:01:28.003360Z

Source-reported events for the cited work

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

Observation e782f5d7-23f5-4673-aa6e-7dd161ecd01c · inbound

Graph Neural Networks in the Wilson Loop Representation of Abelian Lattice Gauge Theories cites this paper.

Graph Neural Networks in the Wilson Loop Representation of Abelian Lattice Gauge Theories MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:51:25.211690Z

Source-reported events for the cited work

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

Observation b238a24c-7e5e-4406-8da8-30bbe93863ff · inbound

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs cites this paper.

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:51:18.133697Z

Source-reported events for the cited work

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

Observation af8d043a-c79f-462d-986d-1670e8e66a3e · inbound

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs cites this paper.

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:47:40.275578Z

Source-reported events for the cited work

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

Observation 410d4c3a-38c5-4bbb-9755-3044ae078796 · inbound

QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space cites this paper.

QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:36:27.545244Z

Source-reported events for the cited work

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

Observation fe8f73b5-78ed-4687-a8ca-3350c0fb58f5 · inbound

Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates cites this paper.

Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:42:03.082057Z

Source-reported events for the cited work

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

Observation ba99bcaf-ae73-43cf-8bc4-5167e79f435e · inbound

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs cites this paper.

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:12:50.690618Z

Source-reported events for the cited work

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

Observation 710f5fe3-fb25-4c4e-905d-85a1c88eff28 · inbound

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs cites this paper.

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:47:40.335385Z

Source-reported events for the cited work

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

Observation 2850a0bc-af76-4f18-9e72-21b455b5b389 · inbound

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks cites this paper.

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:09:43.891822Z

Source-reported events for the cited work

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

Observation 9a116e5d-c384-440e-b00f-4b12050e2d8f · inbound

Disorder-driven symmetry suppression by van der Waals planar defects in a magnetic topological insulator cites this paper.

Disorder-driven symmetry suppression by van der Waals planar defects in a magnetic topological insulator MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:45:50.772647Z

Source-reported events for the cited work

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

Observation a375a8f1-8d92-4ff9-8d17-891b8c8406ad · inbound

Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building cites this paper.

Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-19T19:52:44.405344Z

Source-reported events for the cited work

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

Observation 67573bd5-bc53-4c3f-9cdd-949365d7aee8 · inbound

Anisotropic Crystallization Kinetics and Interfacial Dynamics of Phase-Change Material Sb$_2$S$_3$ from Machine Learning Force Field Simulations cites this paper.

Anisotropic Crystallization Kinetics and Interfacial Dynamics of Phase-Change Material Sb$_2$S$_3$ from Machine Learning Force Field Simulations MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-21T04:33:57.002418Z

Source-reported events for the cited work

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

Observation 5926e3fd-e0ef-420c-a278-034f1633622c · inbound

Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation cites this paper.

Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-22T03:34:34.268787Z

Source-reported events for the cited work

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

Observation 27f9e434-6c2d-411d-a65d-7390142ddb93 · inbound

Multitask learning with semiempirical orbital charges enables sample-efficient MLIPs cites this paper.

Multitask learning with semiempirical orbital charges enables sample-efficient MLIPs MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:54:45.460965Z

Source-reported events for the cited work

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

Observation bd3ebc2a-c907-43c6-b3ce-194dbce682eb · inbound

Loss-Guided Adaptive Scale Refinement for Molecular Force Prediction cites this paper.

Loss-Guided Adaptive Scale Refinement for Molecular Force Prediction MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:57:30.042324Z

Source-reported events for the cited work

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

Observation 13ff02f3-f31c-40d7-a35a-52a64eab81d7 · inbound

Magnetic HIP-NN for spin dynamics in disordered itinerant magnets cites this paper.

Magnetic HIP-NN for spin dynamics in disordered itinerant magnets MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-03T07:57:45.182348Z

Source-reported events for the cited work

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

Observation dda715ed-4609-4f5f-a460-0e9a15553d36 · inbound

Property-Specific Molecular Representations via Feature-Space Transfer Compression cites this paper.

Property-Specific Molecular Representations via Feature-Space Transfer Compression MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:39:39.440970Z

Source-reported events for the cited work

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

Observation 418d2566-9c4c-4edc-8b99-db77df5896dd · inbound

Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages cites this paper.

Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:59:38.100649Z

Source-reported events for the cited work

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

Observation b038e375-23eb-4003-948f-a4afdb658a2e · inbound

Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages cites this paper.

Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T11:04:37.820199Z

Source-reported events for the cited work

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

Observation e5fde15e-8744-4521-8bdb-9c3639a2e1ef · inbound

Constraint-Aware Quantum Optimization of Defect Configurations in Doped ZrO2: XY-Mixer QAOA and Grover Adaptive Search cites this paper.

Constraint-Aware Quantum Optimization of Defect Configurations in Doped ZrO2: XY-Mixer QAOA and Grover Adaptive Search MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:19:43.800848Z

Source-reported events for the cited work

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

Observation 917ad4f5-0931-4771-873f-4f6484435a83 · inbound

A Hybrid Quantum Mechanics Machine Learning Forcefield (QM/ML) Framework for Accurate Solute-Dislocation Interaction Simulations cites this paper.

A Hybrid Quantum Mechanics Machine Learning Forcefield (QM/ML) Framework for Accurate Solute-Dislocation Interaction Simulations MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T03:38:58.570918Z

Source-reported events for the cited work

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

Observation 31b3e04e-af30-4a9c-b27a-2d7c08ea0e73 · inbound

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ cites this paper.

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:53:56.157729Z

Source-reported events for the cited work

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

Observation 30b7b9a0-4e88-45b0-a2f9-40a00d5efd5c · inbound

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ cites this paper.

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T10:04:36.118338Z

Source-reported events for the cited work

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

Observation 797f95c9-39b2-4836-9e59-9d41cc4ecd5b · inbound

Adaptive fine-tuning of foundation models for crystal structure prediction: Discovery of high-pressure phases in the CaFeNi system cites this paper.

Adaptive fine-tuning of foundation models for crystal structure prediction: Discovery of high-pressure phases in the CaFeNi system MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:15:28.088254Z

Source-reported events for the cited work

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

Observation cea3f0dc-b3dc-4fa3-8af5-38aed56cf8b3 · inbound

Full-data accuracy with fewer labels for training and fine-tuning machine-learning force fields cites this paper.

Full-data accuracy with fewer labels for training and fine-tuning machine-learning force fields MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T02:03:18.006449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dc61846-b946-429a-80b6-d50f02d74ad9 · inbound

A fast summation method for the DFT-D3 dispersion correction cites this paper.

A fast summation method for the DFT-D3 dispersion correction MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T00:14:17.866972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1b79fd7-f8d1-469a-a40b-055c00526415 · inbound

Rem3Di: Learning smooth, chiral 3D molecular descriptors from atomistic foundation models cites this paper.

Rem3Di: Learning smooth, chiral 3D molecular descriptors from atomistic foundation models MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T11:16:29.600045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95c03f3e-055f-4d4f-831a-a5089afbc5a6 · inbound

MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance cites this paper.

MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T04:03:29.689156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a066ffa6-a8ea-432d-9f73-f0ed371b9efe · inbound

Fast and Accurate Foundation Models for Equivariant Machine-Learned Interatomic Potentials cites this paper.

Fast and Accurate Foundation Models for Equivariant Machine-Learned Interatomic Potentials MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T06:41:37.838837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7fe8f63-0d76-43f7-97c7-1f575cbed114 · inbound

Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets cites this paper.

Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-31T04:19:36.089465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d028834-b54f-4d44-aece-ffa910526754 · inbound

Predicting large-supercell defect formation energies from machine-learning charge density models trained on small supercells cites this paper.

Predicting large-supercell defect formation energies from machine-learning charge density models trained on small supercells MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T00:39:05.593927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49b40b3c-44a6-4742-a32e-9c56fad4d2eb · inbound

Temperature-Driven Sequential Modeling for the Prediction of Annual Power Conversion Efficiency Profiles of Organic Photovoltaic Materials: Douala Case Study cites this paper.

Temperature-Driven Sequential Modeling for the Prediction of Annual Power Conversion Efficiency Profiles of Organic Photovoltaic Materials: Douala Case Study MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T04:27:31.235381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers