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Category:All HeadlinesWorld & GeopoliticsMarkets & EconomyTech & AIPoliticsSearch results for: "Graph machine learning fo" (30 stories)

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Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy
Lead StoryRSNA Journalsgeneral
May 19

Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy

<a href="https://news.google.com/rss/articles/CBMiXkFVX3lxTFA1N3FhNl83cnlPalBVaDBkY1BpckttamZkdGVfVTRaSVRxQjYwa0ljckhhaVNDaUd0UFRiUVlzWHh3RzQ1aElyWjZhSnI2VThRMXFVWm5kR0IwS1p0NXc?oc=5" target="_blank">Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy</a>  <font color="#6f6f6f">RSNA Journals</font>

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Search Results for "Graph machine learning fo"

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29 stories displayed
DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction
Naturegeneral

DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9XYl84dVI5YThMM194dWFES0NRNHA5UEpnQ09BWHI1QlU2VFlobWJXd2VrNk5Ib1FFR0Y2UDlvRmN6ck9wM09NQ1JYeUlnY2ZiV0ZsUV9RRE11ZnpvS3M0?oc=5" target="_blank">DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction</a>  <font color="#6f6f6f">Nature</font>

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Attribute-guided Dynamic Prompt Learning for Graph Neural Networks
The Association for the Advancement of Artificial Intelligencegeneral

Attribute-guided Dynamic Prompt Learning for Graph Neural Networks

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTFBvR016WUJQOC1vVWowa1R1Z1U2U2R0RlM1N25qaXl0U3RJT08yNzZfd0thS01YT1RfLTdHaG5xaHlIR1g3X2owNHhNck5vTFpIX053eUd6WU5lekkyMlJaOXFCNmw?oc=5" target="_blank">Attribute-guided Dynamic Prompt Learning for Graph Neural Networks</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Real-time dynamic graph learning with temporal attention for financial fraud detection
Frontiersgeneral

Real-time dynamic graph learning with temporal attention for financial fraud detection

<a href="https://news.google.com/rss/articles/CBMiogFBVV95cUxNRzlRWGx1aHpOdUlZeU9tTExwUFdrb1VGQkw2bGhoYjdWMDUxY3VYVDB2bWw2bTN4QWVjM1VCTTI0N0czaGVjRUxrQ3E0dHRndVI0eEJndmxRYTNpT3lBRFExLVhZR08zRTEwNzJWeVpwc2xLMzU3cFVFYkd5VVFzeDNUc1oyX0pxTndkRDdhdVRvbGlGckFzc3NOam00dWpIbFE?oc=5" target="_blank">Real-time dynamic graph learning with temporal attention for financial fraud detection</a>  <font color="#6f6f6f">Frontiers</font>

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Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities
Natureworld

Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE90RWREQTA2SkswbE14cUFLY2R6b0ljbzJQWFJ3REV2c2lwVFVoSVE3SUJvdEF5d3VFMnRvQXBDZF90ZFdXQ3QzOGt6NUNDTzgtSW1EbUhtSmZuTGVLbThZ?oc=5" target="_blank">Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities</a>  <font color="#6f6f6f">Nature</font>

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Learning Fair Graph Representations via Probability of Necessity and Sufficiency
The Association for the Advancement of Artificial Intelligencetech

Learning Fair Graph Representations via Probability of Necessity and Sufficiency

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE1SenVGbTh6NXlzRHozV0U2dVZRSTFNajN4b1hYMXJZaTJQbTZjUFg2bE9Ja3BpZERKMV9vTDY2bDlfTjMtLTF0UWIzUm1nX1ZUQW1SMXVrem04UjFwQkt1SGtyWmQ?oc=5" target="_blank">Learning Fair Graph Representations via Probability of Necessity and Sufficiency</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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A graph-integrated reinforcement learning framework with graph neural networks for tactical decision modeling in professional football
Naturegeneral

A graph-integrated reinforcement learning framework with graph neural networks for tactical decision modeling in professional football

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5vY3NEcmUwVGp5UVloRjVyZ2JSZE9MdTFGbmhqUXlnZWtzU0oxd0NTT0RUTTV6LVpqY3hHU2lyVlZiNlRYakFBZzc5cENLTVBJal9JdDNDeFQwMS0xY2s4?oc=5" target="_blank">A graph-integrated reinforcement learning framework with graph neural networks for tactical decision modeling in professional football</a>  <font color="#6f6f6f">Nature</font>

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Spectral Basis Learning for Expressive Graph Neural Networks in Link Prediction
The Association for the Advancement of Artificial Intelligencegeneral

Spectral Basis Learning for Expressive Graph Neural Networks in Link Prediction

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE9kZFNPNUxBNEJMR2RZVlJYRTkwMnc4ZlBGS0NRZnFxb1Fabk9KY1JDQXAxd0FlcDdBV2E4WkduekF2Y2pZS1FNS0NwWEIwRjlxQXprZjhTdkpWbjBIODlVUWVGT1A?oc=5" target="_blank">Spectral Basis Learning for Expressive Graph Neural Networks in Link Prediction</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Unifying Multi-View Knowledge for Graph Learning via Model Collaboration
The Association for the Advancement of Artificial Intelligenceworld

Unifying Multi-View Knowledge for Graph Learning via Model Collaboration

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE1WV0tYcTVtaU03ajlLSmhxbUU4RjNYNzZvRXREb1VJU2tXSE9hcDlIdXR4WEdOM3VkRVdWWXhiTndQOUdHMnpfOElrNVhSd29uOUl2R0s2OHBJX2Nra3hyNWRqZk0?oc=5" target="_blank">Unifying Multi-View Knowledge for Graph Learning via Model Collaboration</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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VitaGraph: building a knowledge graph for biologically relevant learning tasks | Scientific Data
Naturegeneral

VitaGraph: building a knowledge graph for biologically relevant learning tasks | Scientific Data

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5xZGlVaDlTYVZNVUNJUDVVVVBrT0FBOVhTYkNnSWszYTB2NzRHQ18yTEs0NHdoQjVZb0VIRVM4RmdOZTJDdkZQNkEtbFl3amRXbHlCUzVYYUsxSlNwOWdB?oc=5" target="_blank">VitaGraph: building a knowledge graph for biologically relevant learning tasks | Scientific Data</a>  <font color="#6f6f6f">Nature</font>

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Graph Meets Deep Unfolding: An Interpretable Mutual-benefit Multi-view Learning Network
The Association for the Advancement of Artificial Intelligenceworld

Graph Meets Deep Unfolding: An Interpretable Mutual-benefit Multi-view Learning Network

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE00UjVZeS1KRS1mYTV0dk9GNWJybDJoTDRPa1ZmbUEybjN3X2s3emtlb3Y4bWs2WG1mM1c0LUJMRWhEeU5Zcmp0TTJReFo4LUl0NTQzeGs4QXdPb2cxT1ZUeldURGs?oc=5" target="_blank">Graph Meets Deep Unfolding: An Interpretable Mutual-benefit Multi-view Learning Network</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Rethinking functional brain connectome analysis: do graph deep learning models Help
Naturetech

Rethinking functional brain connectome analysis: do graph deep learning models Help

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFA1QXoxSi1QUEplSnNtRGJDZE9Sa1pBN0NJcDhRcVJTay0xU1dUOGswOVd3SUZBR2dXeVZwV1lQcXpJRlJmeXVfVGx4X2NxMW1TRUo4aGVRVlR6c1NpbVJ3?oc=5" target="_blank">Rethinking functional brain connectome analysis: do graph deep learning models Help</a>  <font color="#6f6f6f">Nature</font>

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Causality-inspired Federated Learning for Dynamic Spatio-Temporal Graphs
The Association for the Advancement of Artificial Intelligencemarkets

Causality-inspired Federated Learning for Dynamic Spatio-Temporal Graphs

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE5zY2ZhVU9wa1BlTE1BcDd3Szd0RVM0RVJqZThla3dJMGdERy1qdkl5ZWJodkFzUlFoNVZmNWtyUzdLTmk0Mlp5WEhrRkc3M1V3cHkxM0JDNjJzT3NpNU52SWMweU4?oc=5" target="_blank">Causality-inspired Federated Learning for Dynamic Spatio-Temporal Graphs</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Meta learning based few shot knowledge graph completion with domain selected aggregation
Naturetech

Meta learning based few shot knowledge graph completion with domain selected aggregation

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE40NmRTaXA1SlFtMDljSWdHb2pFZ29rQ0x3OVN6UUZnQnhPVk80MWFWVThGU1EyNUhhWDE2T1YzR0pqUXB3WGlTZzdPaDNiTEpPVTllQlQwbnVqZFY1djNF?oc=5" target="_blank">Meta learning based few shot knowledge graph completion with domain selected aggregation</a>  <font color="#6f6f6f">Nature</font>

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Deep learning-based high-information-content graph representation of early stage bacterial biofilms
Naturegeneral

Deep learning-based high-information-content graph representation of early stage bacterial biofilms

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9pVUV2WkFicGY2VXMwRXpMa0VFdnVrQmd3cG1UcjMwMlUtbjllSkZqTDVEWEZQTjVNWVlHTENlQXVjYjNMRGFJT0RBYXJuQmNsT0FaZ3lIUFF3ZVgtWlVF?oc=5" target="_blank">Deep learning-based high-information-content graph representation of early stage bacterial biofilms</a>  <font color="#6f6f6f">Nature</font>

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Enhancing molecular property prediction of transformer models with dual graph representation
Naturegeneral

Enhancing molecular property prediction of transformer models with dual graph representation

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFAzenlMT0Q2SjdpR3lQSWtuVEFYUUhrRGZuREJrMzBtalpSOGQ1N2NIU3pkaUdaYTdBZzlWd19OdThXUzNVZURaZUd0SWVqR01nWWxWdUY0X1N0Wm5IS0Vj?oc=5" target="_blank">Enhancing molecular property prediction of transformer models with dual graph representation</a>  <font color="#6f6f6f">Nature</font>

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Knowledge graph-enhanced deep learning for pharmaceutical demand forecasting | Scientific Reports
Naturegeneral

Knowledge graph-enhanced deep learning for pharmaceutical demand forecasting | Scientific Reports

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1uRF9OUTJ1QVdXdGxveUg1d09zMGRzQUZDWnZXNXBOV2pNYjZwRmNLTkJVcUJCNi11SDdBRWFncnRrOEpiMXBycnc3OUFyZGxORHlYem9obHROd2dOUi1F?oc=5" target="_blank">Knowledge graph-enhanced deep learning for pharmaceutical demand forecasting | Scientific Reports</a>  <font color="#6f6f6f">Nature</font>

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Extending the range of graph neural networks with global encodings
Naturegeneral

Extending the range of graph neural networks with global encodings

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE01NmUtVWZUT3V5RDlCeHlBS1ZaTFJOTmEyaFdmTjQtUi1XVGpPenJUcHBKcHFNVU51ZmExSTZIOXlTOW84ZmlIUzNRNjhIS2plcW9SSFpkSnJuMnZscG1J?oc=5" target="_blank">Extending the range of graph neural networks with global encodings</a>  <font color="#6f6f6f">Nature</font>

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AdjLeafGNN: a hybrid deep learning and graph neural network framework for probabilistic modeling of adjacent leaf disease spread in precision agriculture
Naturegeneral

AdjLeafGNN: a hybrid deep learning and graph neural network framework for probabilistic modeling of adjacent leaf disease spread in precision agriculture

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1SRnpmNE1SS0NMOC0zMWVuaGRfQXJEY3I3eEJuLVQ4RzBUMzgwX1d2dnNqLWN4OFpydzF1ckhsMFdGMUZYMHNET1I1ZURHeVpyZ01SS1FucG80UFJVTlc4?oc=5" target="_blank">AdjLeafGNN: a hybrid deep learning and graph neural network framework for probabilistic modeling of adjacent leaf disease spread in precision agriculture</a>  <font color="#6f6f6f">Nature</font>

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Decentralized graph attention multi-agent reinforcement learning for adaptive urban traffic routing
Naturegeneral

Decentralized graph attention multi-agent reinforcement learning for adaptive urban traffic routing

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFAyWlg0NGtpYU9ZemJJeTZBa3l0Q3lLSTJwb095M2Q1dVY4TTQ0RnFVMERXTGlsNjhEMXBYaXRESW54b3dsRlVHSXFGSXN6bGQxLTdmVC1yVUVrX015T0Y0?oc=5" target="_blank">Decentralized graph attention multi-agent reinforcement learning for adaptive urban traffic routing</a>  <font color="#6f6f6f">Nature</font>

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Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning
Naturegeneral

Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9nZUVZc0lGbHRNWnI3TV9RZVd4Y3cxU1Z3ZUFLQkRqZ1hTWXZfVHpPdmlVMUlMcC1rT09DX01ISDRzTEY5WWdoUDhMeEdCOFloQjEtN0d2bEdSLTRxZ0hV?oc=5" target="_blank">Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning</a>  <font color="#6f6f6f">Nature</font>

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Self-Supervised Contrastive Re-Learning for Multi-Graph Multi-Label Classification
The Association for the Advancement of Artificial Intelligencegeneral

Self-Supervised Contrastive Re-Learning for Multi-Graph Multi-Label Classification

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE1jV2dlRjAzWE1vdVBlYjB2dDB1Z2JYWndHRmNhbTdPSmt2ZjBHY0p2dXlJY0xDdEctTFJPV3dQTzdJTEFub3pyY1FqeFVXZ1pCc09XejMzSDgzOEJCeUt5RVJGUnI?oc=5" target="_blank">Self-Supervised Contrastive Re-Learning for Multi-Graph Multi-Label Classification</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Physics-guided contrastive temporal graph learning for anomaly detection and root-cause localization in industrial control systems
Naturegeneral

Physics-guided contrastive temporal graph learning for anomaly detection and root-cause localization in industrial control systems

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1jaml0M29mTjRZdHBkWjMwbTFuT3ZfYk5zcnpJRzRpa2NLOE9oQ2dUTjVwZUF3SC1udVkwcGJFczZHaElYS21mQ1ZqVzRaaF93NHdUVDlGQXBURG5NNm1V?oc=5" target="_blank">Physics-guided contrastive temporal graph learning for anomaly detection and root-cause localization in industrial control systems</a>  <font color="#6f6f6f">Nature</font>

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Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability
Naturegeneral

Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1jdEktdm5wTV9xdU9rd09ocXFVb1lNQnFxNFoydVozYjhaQ2lvc21idktCZ0htUHRkZzhPWjl0LUR2M3lBaXMtTVVNc3FTRVIyLUx6MjRuX1duU3o5Yk9Z?oc=5" target="_blank">Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability</a>  <font color="#6f6f6f">Nature</font>

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A conformational benchmark for optical property prediction with solvent-aware graph neural networks
Naturegeneral

A conformational benchmark for optical property prediction with solvent-aware graph neural networks

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9yVlUtYlR6UWNzVnRDQWR1U0lqdkl0NVFoQlhja1lpYXNLc21RaC05Q2N2anVfcnBSTmlyYVd2aE80ajVfbUVFY21LWnFwelhiWWhBeGRGSWJxY0F0Q293?oc=5" target="_blank">A conformational benchmark for optical property prediction with solvent-aware graph neural networks</a>  <font color="#6f6f6f">Nature</font>

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Graph-based deep learning for drug-drug interaction prediction: a systematic review
Frontiersgeneral

Graph-based deep learning for drug-drug interaction prediction: a systematic review

<a href="https://news.google.com/rss/articles/CBMikAFBVV95cUxONjdHRWJHMVpvenNCYjhtQVE1aW8wV2NMbU1od2VFWEFZb3MzUUdHYmwxOWhFcFoydkQzajF1bjVPUzEtUk1CcWJrQTJjZVJKbTMtNW41eC1yNjZEandmcUJJeVFPLW1mZWJrZUZTR2htYllBMF9JMHFwYzF4Z2FHdlAzUHNYeVllNjhGRmVaMl8?oc=5" target="_blank">Graph-based deep learning for drug-drug interaction prediction: a systematic review</a>  <font color="#6f6f6f">Frontiers</font>

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Reinforcement learning with graph neural network (RL-GNN) fusion for real-time financial fraud detection: a context-aware community mining approach
Natureworld

Reinforcement learning with graph neural network (RL-GNN) fusion for real-time financial fraud detection: a context-aware community mining approach

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1fOElqTWN3UzFZT3oxNjVWWEZwbkFWTTNmMTZNMWFWYnVhTXdtMUpGQ1p4MjQ5N3NzSlQtSmE2NFcyVkRQdDVndGstTDU4M0I5czU5eU9fWWJXdDdnVWFr?oc=5" target="_blank">Reinforcement learning with graph neural network (RL-GNN) fusion for real-time financial fraud detection: a context-aware community mining approach</a>  <font color="#6f6f6f">Nature</font>

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Physics constrained graph neural network for real time prediction of intracranial aneurysm hemodynamics
Naturetech

Physics constrained graph neural network for real time prediction of intracranial aneurysm hemodynamics

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1FWTB6M0taeC1sZVVtTnJqa1dfS0Y0bVJMN0RFOGFpWUhzaG5EOHZSRVRPa1hOVmlWLTZGZUN1OWtOY0N3bE5haWdIMm9xSEc5UjJyYnRJRGRrZlZTV1gw?oc=5" target="_blank">Physics constrained graph neural network for real time prediction of intracranial aneurysm hemodynamics</a>  <font color="#6f6f6f">Nature</font>

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Enhancing knowledge graph recommendations through deep reinforcement learning
Naturegeneral

Enhancing knowledge graph recommendations through deep reinforcement learning

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFByVFJjYUhSWGM5RngwT3JpSHNicml3cF9vSk9BU2M0bWVHNFBxeTZwUWkybVB3WjAyekVtZ2FnUkJkVllsOXZQSE1vR2RBVElVLXNkR0FRMXlpTVJZWkJN?oc=5" target="_blank">Enhancing knowledge graph recommendations through deep reinforcement learning</a>  <font color="#6f6f6f">Nature</font>

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Graph atomic cluster expansion for foundational machine learning interatomic potentials
Natureworld

Graph atomic cluster expansion for foundational machine learning interatomic potentials

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1HeUJXSjVZWFJLS2dmMVQxOUNLcjFjZkRVWmN5WWNLbXduTnVrcjFLUnJ4ZUV4aEFjRHEybUZTY3E2NjVKb3YtWTU2NmJVWDNqM0FaOUpQaXlQaHg2WjNj?oc=5" target="_blank">Graph atomic cluster expansion for foundational machine learning interatomic potentials</a>  <font color="#6f6f6f">Nature</font>

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