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1. 发明公开

EP4416908A1 METHOD FOR DETECTING AND MANAGING NETWORK PER AREA PROPERTIES 审中-实审
公开(公告)号：EP4416908A1
公开(公告)日：2024-08-21
申请号：EP21791366.4
申请日：2021-10-14
申请人： Nokia Technologies Oy
发明人： BEGA, Dario , KUNZMANN, Gerald , GAJIC, Borislava
IPC分类号： H04L41/0893 , H04L41/14 , H04W24/02 , H04L41/16 , H04L41/147
CPC分类号： H04L41/0893 , H04L41/145 , H04L41/16 , H04L41/147

2. 发明公开

EP4297459A1 METHOD AND APPARATUS FOR DETERMINING AND UTILIZING A TRUST INDICATION IN MOBILE NETWORKS 审中-实审
公开(公告)号：EP4297459A1
公开(公告)日：2023-12-27
申请号：EP23178572.6
申请日：2023-06-12
申请人： Nokia Technologies Oy
发明人： GAJIC, Borislava , PEINADO GOMEZ, German , KHARE, Saurabh , SUBRAMANYA, Tejas
IPC分类号： H04W12/60 , H04W12/67 , H04W8/12 , H04W48/18
摘要： Methods and apparatus are disclosed for. A method comprises, collecting information on messages exchanged between a first mobile network and a second mobile network during a time period; and determining a trust indication of the first mobile network at least based on the collected information. The trust indication of the first mobile network indicates a level of trustworthiness of the first mobile network.

3. 发明公开

EP3963829A1 INTEGRATION OF COMMUNICATION NETWORK IN TIME SENSITIVE NETWORKING SYSTEM 审中-实审
公开(公告)号：EP3963829A1
公开(公告)日：2022-03-09
申请号：EP19722568.3
申请日：2019-05-02
申请人： Nokia Technologies Oy
发明人： GANESAN, Rakash SivaSiva , ROST, Peter , MARKWART, Christian , GAJIC, Borislava , MANNWEILER, Christian
IPC分类号： H04L12/24

4. 发明公开

EP4430532A1 TRUSTWORTHY REINFORCEMENT LEARNING 审中-实审
公开(公告)号：EP4430532A1
公开(公告)日：2024-09-18
申请号：EP21811010.4
申请日：2021-11-12
申请人： Nokia Technologies Oy
发明人： GAJIC, Borislava , KHATIBI, Sina , ADAM, Iris , OUTTAGARTS, Abdelkader
IPC分类号： G06N20/00 , H04W24/02 , H04W36/00 , G06N5/02
CPC分类号： G06N20/00 , H04W24/02 , H04W36/0083 , G06N5/022 , H04W36/00833

5. 发明公开

EP4132059A1 AI/ML DATA COLLECTION AND POSSIBLE USAGE FOR MDT 审中-实审
公开(公告)号：EP4132059A1
公开(公告)日：2023-02-08
申请号：EP22185242.9
申请日：2022-07-15
申请人： Nokia Technologies Oy
发明人： PANTELIDOU, Anna , ROST, Peter , GAJIC, Borislava
IPC分类号： H04W24/00 , H04W24/10 , G06N20/00
摘要： A UE transmits a capability message to an access node in a wireless network, indicating capability corresponding to ML of the UE at a current time instance. The UE receives a configuration message for radio measurements, indicating set(s) of parameters to be measured. The UE receives a configured capability in a message and matches the configured capability with the capability of the user equipment at the current time instance. The UE measures the set(s) of parameters. The UE uses ML to infer value(s) for at least one of the parameters based on the measured set(s) of parameters and based on the received configured capability. The UE reports the inferred value(s) for the at least one parameter. An access node receives the capability message, determines and sends the configuration message and configured capability receives the reporting.

6. 发明公开

EP4402963A1 STATUS NOTIFICATIONS OF ACCESS NETWORK FOR TIME SENSITIVE COMMUNICATION 审中-实审
公开(公告)号：EP4402963A1
公开(公告)日：2024-07-24
申请号：EP21957071.0
申请日：2021-09-16
申请人： Nokia Technologies Oy
发明人： GAJIC, Borislava , CHANDRAMOULI, Devaki , SIVASIVA GANESAN, Rakash , CHAO, Hua
IPC分类号： H04W72/04
CPC分类号： H04W76/15 , H04W28/0268 , H04W76/34

7. 发明公开

EP3984182A1 APPARATUS, METHOD AND COMPUTER PROGRAM 审中-公开
公开(公告)号：EP3984182A1
公开(公告)日：2022-04-20
申请号：EP19731698.7
申请日：2019-06-14
申请人： Nokia Technologies Oy
发明人： ROST, Peter , GAJIC, Borislava , MANNWEILER, Christian
IPC分类号： H04L12/801

8. 发明公开

EP3949277A1 FEASIBILITY CHECK FOR NETWORK SLICE INSTANTIATION 审中-实审
公开(公告)号：EP3949277A1
公开(公告)日：2022-02-09
申请号：EP19732902.2
申请日：2019-04-05
申请人： Nokia Technologies Oy
发明人： FENDT, Andrea , GAJIC, Borislava , MANNWEILER, Christian , SCHMELZ, Lars Christoph
IPC分类号： H04L12/24

9. 发明公开

EP4434200A1 CONTROL OF REQUIREMENT FULFILLMENT OF ARTIFICIAL INTELLIGENCE PIPELINES 审中-实审
公开(公告)号：EP4434200A1
公开(公告)日：2024-09-25
申请号：EP21815139.7
申请日：2021-11-15
申请人： Nokia Technologies Oy
发明人： GAJIC, Borislava , SUBRAMANYA, Tejas , ALI-TOLPPA, Janne , SANNECK, Henning
IPC分类号： H04L41/0806 , H04L41/0866 , H04L41/16 , H04L43/08 , H04L41/14 , H04L41/5067 , H04L41/0895 , H04L43/20
CPC分类号： H04L41/16 , H04L41/0866 , H04L41/0806 , H04L43/08 , H04L41/145 , H04L41/5067 , H04L41/0895 , H04L43/20

10. 发明公开

EP4125012A1 TRUST RELATED MANAGEMENT OF ARTIFICIAL INTELLIGENCE OR MACHINE LEARNING PIPELINES IN RELATION TO THE TRUSTWORTHINESS FACTOR EXPLAINABILITY 有权
公开(公告)号：EP4125012A1
公开(公告)日：2023-02-01
申请号：EP22186602.3
申请日：2022-07-25
申请人： Nokia Technologies Oy
发明人： ALI-TOLPPA, Janne , SUBRAMANYA, Tejas , GAJIC, Borislava
IPC分类号： G06N20/20
摘要： There are provided measures for trust related management of artificial intelligence or machine learning pipelines in relation to the trustworthiness factor "explainability". Such measures exemplarily comprise, at a first network entity managing artificial intelligence or machine learning trustworthiness in a network, transmitting a first artificial intelligence or machine learning trustworthiness related message towards a second network entity managing artificial intelligence or machine learning trustworthiness in an artificial intelligence or machine learning pipeline in said network, and receiving a second artificial intelligence or machine learning trustworthiness related message from said second network entity, wherein said first artificial intelligence or machine learning trustworthiness related message is related to artificial intelligence or machine learning model explainability as a trustworthiness factor out of trustworthiness factors including at least artificial intelligence or machine learning model fairness, artificial intelligence or machine learning model explainability, and artificial intelligence or machine learning model robustness, said second artificial intelligence or machine learning trustworthiness related message is related to artificial intelligence or machine learning model explainability as said trustworthiness factor, and said first artificial intelligence or machine learning trustworthiness related message comprises a first information element including at least one first artificial intelligence or machine learning model explainability related parameter.

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