Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:30:48.242196Z
Paper Citation Record · LEDGER
Learning charges and long-range interactions from energies and forces
As of 18 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 4 inbound Pith citation observations for arXiv:2412.15455.
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, observed 2026-08-16T05:20:43.354024Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T16:14:06.257417Z
Reference resolution
64 of 64 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d28b55a7-b94c-4073-aa35-d96934999133 · outbound
This paper cites Long range interactions in nanoscale science,.
Learning charges and long-range interactions from energies and forces Long range interactions in nanoscale science,
Reference 1
- Resolution
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Source-reported events for the cited work
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Observation 95bc81af-75b7-4b20-8e2a-51bde035bf9c · outbound
This paper cites Efficient cluster expansion for substitutional systems,.
Learning charges and long-range interactions from energies and forces Efficient cluster expansion for substitutional systems,
Reference 2
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 14511e04-cd43-428b-bbb7-b5a5d5e5bd9f · outbound
This paper cites Charge scaling manifesto: A way of reconciling the inherently macro- scopic and microscopic natures of molecular simulations,.
Learning charges and long-range interactions from energies and forces Charge scaling manifesto: A way of reconciling the inherently macro- scopic and microscopic natures of molecular simulations,
Reference 3
- Resolution
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Source-reported events for the cited work
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Observation be42c149-90b1-460e-b0ac-570001fe0e72 · outbound
This paper cites Influence of surface topology and electrostatic potential on water/electrode systems,.
Learning charges and long-range interactions from energies and forces Influence of surface topology and electrostatic potential on water/electrode systems,
Reference 4
- Resolution
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Source-reported events for the cited work
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Observation 4b85c211-b617-4949-aed3-e8ff5aa32801 · outbound
This paper cites Combining machine learning and computational chemistry for pre- dictive insights into chemical systems,.
Learning charges and long-range interactions from energies and forces Combining machine learning and computational chemistry for pre- dictive insights into chemical systems,
Reference 5
- Resolution
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Source-reported events for the cited work
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Observation 6f1df445-46c0-43e3-b1a2-189d615c18d9 · outbound
This paper cites Ma- chine learning force fields,.
Learning charges and long-range interactions from energies and forces Ma- chine learning force fields,
Reference 6
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Source-reported events for the cited work
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Observation 1df34a78-21b2-43ea-b25a-7646f95fae69 · outbound
This paper cites Learning intermolecular forces at liquid–vapor inter- faces,.
Learning charges and long-range interactions from energies and forces Learning intermolecular forces at liquid–vapor inter- faces,
Reference 7
- Resolution
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Source-reported events for the cited work
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Observation ee567043-1824-42a6-9b77-4ce78cb22d6c · outbound
This paper cites Incorporating long-range physics in atomic-scale machine learning,.
Learning charges and long-range interactions from energies and forces Incorporating long-range physics in atomic-scale machine learning,
Reference 8
- Resolution
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Source-reported events for the cited work
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Observation 2dd30be3-2700-4ce1-9972-501ddc7b5f90 · outbound
This paper cites Physics-inspired equivariant descriptors of nonbonded interactions,.
Learning charges and long-range interactions from energies and forces Physics-inspired equivariant descriptors of nonbonded interactions,
Reference 9
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 576b9ce7-a907-42d6-ae3f-b2d5f530a7a3 · outbound
This paper cites A deep potential model with long-range electrostatic inter- actions,.
Learning charges and long-range interactions from energies and forces A deep potential model with long-range electrostatic inter- actions,
Reference 10
- Resolution
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Source-reported events for the cited work
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Observation b12e1577-a4f9-405e-afb9-5a0212cae1ee · outbound
This paper cites Electrostatic interactions in atomistic and machine-learned potentials for polar materials.
Learning charges and long-range interactions from energies and forces Electrostatic interactions in atomistic and machine-learned potentials for polar materials
Reference 11
- Resolution
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Source-reported events for the cited work
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Observation 8f8b33f3-07fc-42a1-ade5-7d51f0879b11 · outbound
This paper cites A fourth-generation high-dimensional neu- ral network potential with accurate electrostatics includ- ing non-local charge transfer,.
Learning charges and long-range interactions from energies and forces A fourth-generation high-dimensional neu- ral network potential with accurate electrostatics includ- ing non-local charge transfer,
Reference 12
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93cd6338-0252-4377-bd70-927e742abed8 · outbound
This paper cites Physnet: A neu- ral network for predicting energies, forces, dipole mo- ments, and partial charges,.
Learning charges and long-range interactions from energies and forces Physnet: A neu- ral network for predicting energies, forces, dipole mo- ments, and partial charges,
Reference 13
- Resolution
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Source-reported events for the cited work
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Observation e828ea26-6c30-4648-9db8-ed7e51876e37 · outbound
This paper cites Self-consistent deter- mination of long-range electrostatics in neural network potentials,.
Learning charges and long-range interactions from energies and forces Self-consistent deter- mination of long-range electrostatics in neural network potentials,
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 8b887851-6f99-4aff-b5f2-0d5aa76efdf5 · outbound
This paper cites Discovering a transferable charge assignment model us- ing machine learning,.
Learning charges and long-range interactions from energies and forces Discovering a transferable charge assignment model us- ing machine learning,
Reference 15
- Resolution
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Source-reported events for the cited work
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Observation 2db49cbc-8ba9-4073-a901-7a78077c8008 · outbound
This paper cites A predictive machine learning force field framework for liquid electrolyte development.
Learning charges and long-range interactions from energies and forces A predictive machine learning force field framework for liquid electrolyte development
Reference 16
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 324026bf-48b1-42a9-a072-2de18a41e618 · outbound
This paper cites Incorporating long-range electrostatics in neural network potentials via variational charge equilibration from shortsighted ingre- dients,.
Learning charges and long-range interactions from energies and forces Incorporating long-range electrostatics in neural network potentials via variational charge equilibration from shortsighted ingre- dients,
Reference 17
- Resolution
- verified fuzzy
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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 7cba4ebe-7044-4828-ae8d-e36f21b145ca · outbound
This paper cites Charge equilibration for molecular dynamics simulations,.
Learning charges and long-range interactions from energies and forces Charge equilibration for molecular dynamics simulations,
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation b345acb5-048b-492a-8e6f-1832c9951188 · outbound
This paper cites Capturing long-range interaction with reciprocal space neural network.
Learning charges and long-range interactions from energies and forces Capturing long-range interaction with reciprocal space neural network
Reference 19
- Resolution
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Source-reported events for the cited work
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Observation da7f17b1-6f7c-4db2-9e01-df92cdc0256e · outbound
This paper cites Ewald-based long-range message passing for molecular graphs,.
Learning charges and long-range interactions from energies and forces Ewald-based long-range message passing for molecular graphs,
Reference 20
- Resolution
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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 1805beb8-7acb-4103-886b-d42f3a548b68 · outbound
This paper cites Density-Based Long-Range Electrostatic Descriptors for Machine Learning Force Fields.
Learning charges and long-range interactions from energies and forces Density-Based Long-Range Electrostatic Descriptors for Machine Learning Force Fields
Reference 21
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5d4bd742-889a-4159-8319-4cceb874c1f0 · outbound
This paper cites Fast and flexible long-range models for atomistic machine learning.
Learning charges and long-range interactions from energies and forces Fast and flexible long-range models for atomistic machine learning
Reference 22
- Resolution
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Source-reported events for the cited work
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Observation 912660bb-e6ae-4320-8575-eb4279d76995 · outbound
This paper cites Latent Ewald summation for machine learning of long-range interactions.
Learning charges and long-range interactions from energies and forces Latent Ewald summation for machine learning of long-range interactions
Reference 23
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83a8e9ef-779d-4441-a8d2-e6bb331d335d · outbound
This paper cites Generalized neural- network representation of high-dimensional potential- energy surfaces,.
Learning charges and long-range interactions from energies and forces Generalized neural- network representation of high-dimensional potential- energy surfaces,
Reference 24
- Resolution
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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 6b6ebed5-5c8c-4bf4-adc6-014a369a0ef2 · outbound
This paper cites Gaussian approximation potentials: The ac- curacy of quantum mechanics, without the electrons,.
Learning charges and long-range interactions from energies and forces Gaussian approximation potentials: The ac- curacy of quantum mechanics, without the electrons,
Reference 25
- Resolution
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Source-reported events for the cited work
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Observation 31155c2a-2416-4608-b078-761c0bdf8a51 · outbound
This paper cites Moment tensor potentials: A class of systematically improvable interatomic poten- tials,.
Learning charges and long-range interactions from energies and forces Moment tensor potentials: A class of systematically improvable interatomic poten- tials,
Reference 26
- Resolution
- verified fuzzy
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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 f6c52038-17b3-4016-b768-d2e47a3b4c93 · outbound
This paper cites Atomic cluster expansion for accurate and transferable interatomic potentials,.
Learning charges and long-range interactions from energies and forces Atomic cluster expansion for accurate and transferable interatomic potentials,
Reference 27
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff46d0b3-c65e-4b65-a576-aba750474d2f · outbound
This paper cites E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials,.
Learning charges and long-range interactions from energies and forces E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials,
Reference 28
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f776b3a-6a8f-4a89-9f65-d175e1ef27d3 · outbound
This paper cites Mace: Higher order equiv- ariant message passing neural networks for fast and ac- curate force fields,.
Learning charges and long-range interactions from energies and forces Mace: Higher order equiv- ariant message passing neural networks for fast and ac- curate force fields,
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 4a235b22-d5b9-4773-b136-ff0ed53f23a0 · outbound
This paper cites Cartesian atomic cluster expansion for machine learning interatomic potentials,.
Learning charges and long-range interactions from energies and forces Cartesian atomic cluster expansion for machine learning interatomic potentials,
Reference 30
- Resolution
- verified fuzzy
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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 cd1f8950-6c99-4953-ac5e-5b7dab83cc3d · outbound
This paper cites Schnet: A continuous-filter convolutional neural network for modeling quantum in- teractions,.
Learning charges and long-range interactions from energies and forces Schnet: A continuous-filter convolutional neural network for modeling quantum in- teractions,
Reference 31
- Resolution
- verified fuzzy
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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 20489adc-9048-485a-9cfc-557e4f5bcd0e · outbound
This paper cites Chgnet as a pretrained universal neural network potential for charge-informed atomistic mod- elling,.
Learning charges and long-range interactions from energies and forces Chgnet as a pretrained universal neural network potential for charge-informed atomistic mod- elling,
Reference 32
- Resolution
- verified fuzzy
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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 96731424-c15d-42f4-901f-15304eeff662 · outbound
This paper cites Newtonnet: A newtonian message pass- ing network for deep learning of interatomic potentials and forces,.
Learning charges and long-range interactions from energies and forces Newtonnet: A newtonian message pass- ing network for deep learning of interatomic potentials and forces,
Reference 33
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation ae292b3e-86df-497d-bfc6-586e84e898d6 · outbound
This paper cites Accelerated convergence of crystal- lattice potential sums,.
Learning charges and long-range interactions from energies and forces Accelerated convergence of crystal- lattice potential sums,
Reference 34
- Resolution
- verified fuzzy
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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 a19cb341-a1cd-45e3-85a1-65e5657b0e26 · outbound
This paper cites Nearsightedness of elec- tronic matter,.
Learning charges and long-range interactions from energies and forces Nearsightedness of elec- tronic matter,
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 3796de84-bee7-4213-9965-cc6f91e96871 · outbound
This paper cites Flexible simple point-charge water model with improved liquid-state properties,.
Learning charges and long-range interactions from energies and forces Flexible simple point-charge water model with improved liquid-state properties,
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.773952Z
Source-reported events for the cited work
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Observation 679ee7dd-2def-4cc0-9f8b-728e02ca4d58 · outbound
This paper cites Determina- tion of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations,.
Learning charges and long-range interactions from energies and forces Determina- tion of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.760167Z
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 4e24bbac-8717-45fa-a9a6-696de75463c4 · outbound
This paper cites The biofragment database (bfdb): An open- data platform for computational chemistry analysis of noncovalent interactions,.
Learning charges and long-range interactions from energies and forces The biofragment database (bfdb): An open- data platform for computational chemistry analysis of noncovalent interactions,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.746389Z
Source-reported events for the cited work
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Observation c43e52a6-8648-467b-951f-b978ab97c56a · outbound
This paper cites Spice, a dataset of drug-like molecules and peptides for training machine learning potentials,.
Learning charges and long-range interactions from energies and forces Spice, a dataset of drug-like molecules and peptides for training machine learning potentials,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.732157Z
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 d1830de0-007e-4207-826a-5e946f4aa896 · outbound
This paper cites free lunch.
Learning charges and long-range interactions from energies and forces free lunch
Reference 40
- Resolution
- verified fuzzy
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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 7bfc0e9e-8f46-4eca-b03d-1072cce8b18d · outbound
This paper cites Minimal basis iterative stockholder: atoms in molecules for force-field development,.
Learning charges and long-range interactions from energies and forces Minimal basis iterative stockholder: atoms in molecules for force-field development,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.718350Z
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 b06b3886-3c25-4f9d-abe7-0693130f9a12 · outbound
This paper cites Charge-constrained Atomic Cluster Expansion.
Learning charges and long-range interactions from energies and forces Charge-constrained Atomic Cluster Expansion
Reference 42
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4b20ee2-a0dd-44cc-89db-0880de52bcdc · outbound
This paper cites Atomic cluster expansion: Complete- ness, efficiency and stability,.
Learning charges and long-range interactions from energies and forces Atomic cluster expansion: Complete- ness, efficiency and stability,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.705116Z
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 2ed70918-ccd1-4990-bc39-d2eba051ae9c · outbound
This paper cites Bonded-atom fragments for describing molecular charge densities,.
Learning charges and long-range interactions from energies and forces Bonded-atom fragments for describing molecular charge densities,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.692801Z
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 2299fd21-e525-48d9-8388-21c850194897 · outbound
This paper cites Machine Learning Potential for Electrochemical Interfaces with Hybrid Representation of Dielectric Response.
Learning charges and long-range interactions from energies and forces Machine Learning Potential for Electrochemical Interfaces with Hybrid Representation of Dielectric Response
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:30:48.159596Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 278b3c38-0f5c-4b43-943d-41c63a6f189e · outbound
This paper cites Electrical double layer and capacitance of TiO2 electrolyte interfaces from first principles simulations.
Learning charges and long-range interactions from energies and forces Electrical double layer and capacitance of TiO2 electrolyte interfaces from first principles simulations
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:30:48.163596Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1435cf80-e72f-46dd-80a7-c9ad513a46ad · outbound
This paper cites Incompleteness of atomic structure represen- tations,.
Learning charges and long-range interactions from energies and forces Incompleteness of atomic structure represen- tations,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.680535Z
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 4fc7ad9c-65e4-482e-90be-1d13ca38b133 · outbound
This paper cites Observing and Modeling the Sequential Pairwise Re- actions that Drive Solid-State Ceramic Synthesis,.
Learning charges and long-range interactions from energies and forces Observing and Modeling the Sequential Pairwise Re- actions that Drive Solid-State Ceramic Synthesis,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.666754Z
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 a3dd32ce-d2a5-43e8-898f-040d15df298d · outbound
This paper cites What dictates soft clay-like lithium superionic conduc- tor formation from rigid salts mixture,.
Learning charges and long-range interactions from energies and forces What dictates soft clay-like lithium superionic conduc- tor formation from rigid salts mixture,
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.653142Z
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 4b468151-ed9c-4633-8fb7-d8c785d7a7ec · outbound
This paper cites Uncertainty Quantification and Propagation in Atomistic Machine Learning.
Learning charges and long-range interactions from energies and forces Uncertainty Quantification and Propagation in Atomistic Machine Learning
Reference 50
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T11:30:48.286544Z
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 f6c53f34-3412-4e63-81f8-34e013e0929b · outbound
This paper cites Fast uncertainty estimates in deep learning interatomic potentials,.
Learning charges and long-range interactions from energies and forces Fast uncertainty estimates in deep learning interatomic potentials,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.639682Z
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 c26323e7-6243-476d-9ae8-d22aabad80c6 · outbound
This paper cites A theoretically grounded application of dropout in recurrent neural net- works,.
Learning charges and long-range interactions from energies and forces A theoretically grounded application of dropout in recurrent neural net- works,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.625302Z
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 111b2795-13e1-4ce9-922a-91dd2fc3e769 · outbound
This paper cites Deep evidential regression,.
Learning charges and long-range interactions from energies and forces Deep evidential regression,
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.611663Z
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 64805331-f132-4e4f-9f3e-4c9641cb067a · outbound
This paper cites Comparison of atomic charges derived via different procedures,.
Learning charges and long-range interactions from energies and forces Comparison of atomic charges derived via different procedures,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.597977Z
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 cbef22ea-9dbf-4806-b5dd-3b5d34dac568 · outbound
This paper cites Charge model 5: An extension of hirshfeld population analysis for the accu- rate description of molecular interactions in gaseous and condensed phases,.
Learning charges and long-range interactions from energies and forces Charge model 5: An extension of hirshfeld population analysis for the accu- rate description of molecular interactions in gaseous and condensed phases,
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.583475Z
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 26056ea5-0261-41c8-8c4b-96e0e278ef78 · outbound
This paper cites Electronic population analysis on lcao–mo molecular wave functions. i,.
Learning charges and long-range interactions from energies and forces Electronic population analysis on lcao–mo molecular wave functions. i,
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.569090Z
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 b9027b74-ae48-473d-9f56-42872249fd3f · outbound
This paper cites Dynamical matrices, born effective charges, dielectric permittivity tensors, and interatomic force constants from density-functional per- turbation theory,.
Learning charges and long-range interactions from energies and forces Dynamical matrices, born effective charges, dielectric permittivity tensors, and interatomic force constants from density-functional per- turbation theory,
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.555043Z
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 8a6e73ad-0e7a-4a54-8f83-4d9aea19d2d0 · outbound
This paper cites First-principles predic- tion of vacancy order-disorder and intercalation battery voltages in Li xCoO2,.
Learning charges and long-range interactions from energies and forces First-principles predic- tion of vacancy order-disorder and intercalation battery voltages in Li xCoO2,
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.540306Z
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 bae6d63d-abb7-4370-b88f-3b48b7cc3242 · outbound
This paper cites Charge self-regulation upon changing the oxidation state of transition metals in insulators,.
Learning charges and long-range interactions from energies and forces Charge self-regulation upon changing the oxidation state of transition metals in insulators,
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.525079Z
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 e9490454-950e-4b85-a6ef-ea51cc8ea4e9 · outbound
This paper cites Oxidation states and ionicity,.
Learning charges and long-range interactions from energies and forces Oxidation states and ionicity,
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.508796Z
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 a4845c8d-1ba6-42f4-a0ec-e93cd533ff2c · outbound
This paper cites Active learn- ing of reactive Bayesian force fields applied to heteroge- neous catalysis dynamics of H/Pt,.
Learning charges and long-range interactions from energies and forces Active learn- ing of reactive Bayesian force fields applied to heteroge- neous catalysis dynamics of H/Pt,
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.495679Z
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 077aad57-6c1b-4046-87c2-58d5b63c68a6 · outbound
This paper cites Python Materials Genomics (py- matgen): A robust, open-source python library for ma- terials analysis,.
Learning charges and long-range interactions from energies and forces Python Materials Genomics (py- matgen): A robust, open-source python library for ma- terials analysis,
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.482590Z
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 8b4bd693-bb20-4cd1-b9df-fb81b0c407bc · outbound
This paper cites Generalized gradient approximation made simple,.
Learning charges and long-range interactions from energies and forces Generalized gradient approximation made simple,
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.469298Z
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 ec30bbfe-b97f-4884-9c46-9e8a9e7dd2dc · outbound
This paper cites A consistent and accurate ab initio parametrization of density functional dispersion correc- tion (dft-d) for the 94 elements h-pu,.
Learning charges and long-range interactions from energies and forces A consistent and accurate ab initio parametrization of density functional dispersion correc- tion (dft-d) for the 94 elements h-pu,
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T11:30:48.455116Z
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
Observation d81dff19-c240-4583-b5c7-f9af09052196 · 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 Learning charges and long-range interactions from energies and forces
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T21:05:47.593529Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e4c5441-7ba6-4174-80b4-0baad0e2821d · inbound
Egret-1: Pretrained Neural Network Potentials for Efficient and Accurate Bioorganic Simulation cites this paper.
Egret-1: Pretrained Neural Network Potentials for Efficient and Accurate Bioorganic Simulation Learning charges and long-range interactions from energies and forces
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T05:20:43.354024Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0739db44-dee7-4033-b2b1-e32fef659567 · inbound
Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications cites this paper.
Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Learning charges and long-range interactions from energies and forces
Reference 127
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:23:19.482942Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f697515d-0c43-4937-ba37-31d0556a8ea6 · inbound
A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials cites this paper.
A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials Learning charges and long-range interactions from energies and forces
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T16:14:06.337480Z
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.