Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting | Paper Citation Record

Observation a42c893b-0a23-42d5-bd92-b0d1e11bdda1 · outbound

This paper cites Characterizing and modeling internet traffic dy- namics of cellular devices,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Characterizing and modeling internet traffic dy- namics of cellular devices,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.999999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d0f54c1c-9cd5-4626-8d37-2bbff552039b · outbound

This paper cites Machine learning for networking: Workflow, advances and opportunities,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Machine learning for networking: Workflow, advances and opportunities,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.987589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b86ea59e-0cfc-4283-b34a-bdc088387f62 · outbound

This paper cites Building a digital twin for network optimiza- tion using graph neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Building a digital twin for network optimiza- tion using graph neural networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.974242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8171f0b4-29af-4ddf-a2fd-a5cf170032e8 · outbound

This paper cites Traffic flow prediction with big data: a deep learning approach,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Traffic flow prediction with big data: a deep learning approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.961193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 17a30370-653b-4924-bd92-6aba52e48b1a · outbound

This paper cites Deep learning on traffic prediction: Methods, analysis and future directions,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Deep learning on traffic prediction: Methods, analysis and future directions,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.947861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b8e180d3-f620-464a-abb6-11da5ac3698a · outbound

This paper cites Long-term mobile traffic forecasting using deep spatio-temporal neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Long-term mobile traffic forecasting using deep spatio-temporal neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.934647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2e1a4246-cd35-4d5f-bf05-fc8a952c1a25 · outbound

This paper cites How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.227001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c5780e-0ae5-42ce-9015-25e8bd104bf4 · outbound

This paper cites Mobile Traffic Forecasting for Green 5G Networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Mobile Traffic Forecasting for Green 5G Networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.922442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dc24f661-7804-4936-aefe-ee4c5d483cc8 · outbound

This paper cites Forecasting mobile traffic to achieve greener 5G net- works: When machine learning is key,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Forecasting mobile traffic to achieve greener 5G net- works: When machine learning is key,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.908784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b7329844-97a8-48a3-9fa0-2fe56ae26196 · outbound

This paper cites Estimating energy consumption of cloud, fog, and edge computing infrastructures,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Estimating energy consumption of cloud, fog, and edge computing infrastructures,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.896283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 152fe580-ebf7-4595-adfd-b95cd8b75ca9 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Communication-efficient learning of deep networks from decentralized data,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.242407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cf5a908-0d2a-4344-8177-4657df1e4ac6 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Federated Learning: Strategies for Improving Communication Efficiency

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.246309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c77cb802-d4c5-4ac8-8c62-91417a6071bd · outbound

This paper cites Federated learning for 5G base station traffic forecasting,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Federated learning for 5G base station traffic forecasting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.876335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 04256a0a-193f-40a0-8339-6a392284c29c · outbound

This paper cites Mobile traffic classification through physical control channel fingerprinting: a deep learning approach,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Mobile traffic classification through physical control channel fingerprinting: a deep learning approach,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.864999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0acff08e-c52e-450e-8939-b0d9ba6eef29 · outbound

This paper cites Time series analysis: Forecasting and control San Francisco,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Time series analysis: Forecasting and control San Francisco,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.853599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 72d7dc5c-8501-43fd-85d4-bd6cb3e477c6 · outbound

This paper cites Neural network models for time series forecasts,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Neural network models for time series forecasts,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.841610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d22c8d52-d269-4921-997f-8b785ceddbbe · outbound

This paper cites Recurrent neural network based language model,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Recurrent neural network based language model,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.829939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 74eb18dd-6b60-4e32-ab3a-3a4273e24142 · outbound

This paper cites Speech recognition with deep recurrent neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Speech recognition with deep recurrent neural networks,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.268395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2a5dab9-9caa-4cf3-8715-8b447c269100 · outbound

This paper cites Deepfake video detection using recurrent neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Deepfake video detection using recurrent neural networks,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.271951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7952e769-33a5-48dd-bc8e-038b571d0db7 · outbound

This paper cites Mobile traffic prediction from raw data using LSTM networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Mobile traffic prediction from raw data using LSTM networks,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.275574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc7db26c-0032-4389-9347-e9b5445d7ec7 · outbound

This paper cites Urban anomaly detection by processing mobile traffic traces with LSTM neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Urban anomaly detection by processing mobile traffic traces with LSTM neural networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.797304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4c70feb6-6d88-4bbd-bb89-a4f9a7c8e4cd · outbound

This paper cites Spatio-temporal wireless traffic prediction with recurrent neural network,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Spatio-temporal wireless traffic prediction with recurrent neural network,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.785880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8f8e5d7a-6e3f-4826-bd51-12d86ed7146f · outbound

This paper cites Recent advances in convolutional neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Recent advances in convolutional neural networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.773996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 25f702eb-0dcc-49b4-9fec-400927332643 · outbound

This paper cites Network traffic prediction based on diffusion convolutional recurrent neural networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Network traffic prediction based on diffusion convolutional recurrent neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.761594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1ecd2b1a-67f1-442d-9072-f7515f9bf7bd · outbound

This paper cites Deep residual learning for image recognition,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Deep residual learning for image recognition,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.750357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0fd6a350-a270-4055-b720-35a411ff685b · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.297483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation faa096ce-33f6-42c6-a2d6-4e8dd465f2bb · outbound

This paper cites A multivariate-time-series-prediction-based adaptive data transmission period control algorithm for iot networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting A multivariate-time-series-prediction-based adaptive data transmission period control algorithm for iot networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.737960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8fc9fb82-5609-4dc6-b57c-3f4b60386bc3 · outbound

This paper cites Towards energy-aware federated traffic prediction for cellular networks,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Towards energy-aware federated traffic prediction for cellular networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.725505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c2e53c5a-3b49-498c-b7a1-5cb29466a821 · outbound

This paper cites Privacy-preserving traffic flow prediction: A federated learning approach,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Privacy-preserving traffic flow prediction: A federated learning approach,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.308276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbe36e02-b73f-4160-9034-5402ce803ed0 · outbound

This paper cites Multi-task federated learning for traffic prediction and its application to route planning,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Multi-task federated learning for traffic prediction and its application to route planning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.707281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b5472ece-d4c6-4177-befa-25e646dcdaaf · outbound

This paper cites Dual attention-based federated learning for wireless traffic prediction,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Dual attention-based federated learning for wireless traffic prediction,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.696679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a10383d9-61b4-4eb9-95eb-808a9accbcf8 · outbound

This paper cites Efficient wireless traffic prediction at the edge: A federated meta-learning approach,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Efficient wireless traffic prediction at the edge: A federated meta-learning approach,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.685892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a54489ee-f015-45d2-9510-87972884e28d · outbound

This paper cites A multi-source dataset of urban life in the city of Milan and the Province of Trentino,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting A multi-source dataset of urban life in the city of Milan and the Province of Trentino,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.673364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4683b55d-ff1b-41d0-89ff-28a1c07a3355 · outbound

This paper cites Federated learning: Challenges, methods, and future directions,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Federated learning: Challenges, methods, and future directions,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.662166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f564519c-14df-4ab5-a499-be177768f54a · outbound

This paper cites Maverick matters: Client contribution and selection in federated learning,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Maverick matters: Client contribution and selection in federated learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.650591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ba181324-5091-43b0-b857-bef82078dcb0 · outbound

This paper cites Toward understanding the influence of individual clients in federated learning,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Toward understanding the influence of individual clients in federated learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.638368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5f89d727-4215-4641-936e-714b49ca9392 · outbound

This paper cites A deep-learning model for urban traffic flow prediction with traffic events mined from twitter,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting A deep-learning model for urban traffic flow prediction with traffic events mined from twitter,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.625803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 362dd569-e050-47a3-87ec-1c38ae7ec7f9 · outbound

This paper cites Graph attention spatial-temporal network with collabora- tive global-local learning for citywide mobile traffic prediction,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Graph attention spatial-temporal network with collabora- tive global-local learning for citywide mobile traffic prediction,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.612848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eee216c1-ee93-4347-900f-75590d99503d · outbound

This paper cites The Cost of Training Machine Learning Models over Distributed Data Sources,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting The Cost of Training Machine Learning Models over Distributed Data Sources,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.599943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9760946e-d23a-4277-80b7-822cc43d075d · outbound

This paper cites Long short-term memory,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Long short-term memory,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.587947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 038aa672-58fd-4ef9-b9d9-3090a1d97231 · outbound

This paper cites an unresolved cited work.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:50:55.575665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2d84a037-97ba-41e9-bd0c-d09d31868c59 · outbound

This paper cites Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.358507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f3a2eb9-a478-416d-bb1b-9028b705ab20 · outbound

This paper cites Isolation forest,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Isolation forest,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.362512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d917a2d9-f486-4271-8cdf-255591160f93 · outbound

This paper cites Alternatives to the median absolute deviation,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Alternatives to the median absolute deviation,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.556266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation acd62c9b-533b-4b70-b727-32c34f5ca059 · outbound

This paper cites Robust outlier detection using svm regression,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Robust outlier detection using svm regression,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.543095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fa3aadaa-b00f-415c-88e3-28e925e2f532 · outbound

This paper cites A review on outlier/anomaly detection in time series data,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting A review on outlier/anomaly detection in time series data,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.529539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 990052d5-f48a-4972-87b7-f3dbb511a1b0 · outbound

This paper cites Tackling the objective inconsistency problem in het- erogeneous federated optimization,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Tackling the objective inconsistency problem in het- erogeneous federated optimization,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.516592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4f3417a6-53ae-4356-b48d-33296bb663c9 · outbound

This paper cites Federated visual classification with real-world data distribution,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Federated visual classification with real-world data distribution,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.504360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dd8dd172-fe3f-4e34-9ced-06139e83b715 · outbound

This paper cites Adaptive Federated Optimization.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Adaptive Federated Optimization

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T21:50:55.383096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25c0b243-93cf-482c-a36c-291d853e8b03 · outbound

This paper cites Amplitude-aligned personalization and robust aggregation for federated learning,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Amplitude-aligned personalization and robust aggregation for federated learning,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.493521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2bbdc947-b071-4fda-ba89-d880d052474a · outbound

This paper cites Upgini - automated data search & enrichment library,.

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting Upgini - automated data search & enrichment library,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:50:55.481085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers