A Survey on Machine and Deep Learning for Optical Communications | Paper Citation Record

Observation eba74bbb-fd32-4550-b51a-5ac09ee519fe · outbound

This paper cites Supervised Learning.

A Survey on Machine and Deep Learning for Optical Communications Supervised Learning

Reference 1

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This paper cites On-line Support Vector Machine Regression.

A Survey on Machine and Deep Learning for Optical Communications On-line Support Vector Machine Regression

Reference 2

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Observation f7fb74a9-2b88-4368-8938-a09815bc3407 · outbound

This paper cites Artificial Neural Networks.

A Survey on Machine and Deep Learning for Optical Communications Artificial Neural Networks

Reference 3

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Observation b8795334-7fe6-4e79-8e31-76fa5cb96d3d · outbound

This paper cites An Efficient Instance Selection Algorithm for k Nearest Neighbor Regression.

A Survey on Machine and Deep Learning for Optical Communications An Efficient Instance Selection Algorithm for k Nearest Neighbor Regression

Reference 4

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Observation 651b6fc1-7277-4152-b12c-373268fd78de · outbound

This paper cites Ensemble Learning.

A Survey on Machine and Deep Learning for Optical Communications Ensemble Learning

Reference 5

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Observation 16ab2f5b-2dbf-4790-9647-1b013d8958d8 · outbound

This paper cites Linear Regression Analysis.

A Survey on Machine and Deep Learning for Optical Communications Linear Regression Analysis

Reference 6

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Observation 5a42b712-8323-4f40-8120-ee9bd3d99e1f · outbound

This paper cites Ridge regression: some simulations.

A Survey on Machine and Deep Learning for Optical Communications Ridge regression: some simulations

Reference 7

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Observation df31c6ec-c0d8-42d7-bc06-715f5f80c239 · outbound

This paper cites LASSO regression.

A Survey on Machine and Deep Learning for Optical Communications LASSO regression

Reference 8

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Observation 522b504e-3f1f-460a-9413-cd9bd3aca1d0 · outbound

This paper cites Unsupervised learning.

A Survey on Machine and Deep Learning for Optical Communications Unsupervised learning

Reference 9

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Observation 360e0a49-c2d4-47ef-b417-1e8c1076b9ec · outbound

This paper cites Introduction to HPC with MPI for Data Science.

A Survey on Machine and Deep Learning for Optical Communications Introduction to HPC with MPI for Data Science

Reference 10

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Observation e736409d-2e4b-4076-b1d2-5ccab4bd749b · outbound

This paper cites Unsupervised K-means clustering algorithm.

A Survey on Machine and Deep Learning for Optical Communications Unsupervised K-means clustering algorithm

Reference 11

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Observation b7487fc6-116e-4b64-a60b-deb68928501b · outbound

This paper cites What is the expectation maximization algorithm?.

A Survey on Machine and Deep Learning for Optical Communications What is the expectation maximization algorithm?

Reference 12

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Observation e4e69cb9-8004-4b91-9ca2-bc5a6452cfd5 · outbound

This paper cites Principal component analysis.

A Survey on Machine and Deep Learning for Optical Communications Principal component analysis

Reference 13

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Observation 12556d3e-734b-47c7-9f39-8d694e55849a · outbound

This paper cites Independent component analysis: an introduction.

A Survey on Machine and Deep Learning for Optical Communications Independent component analysis: an introduction

Reference 14

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Observation 3c2298ce-3890-41c9-a2c8-17994a2706f7 · outbound

This paper cites Reinforcement learning.

A Survey on Machine and Deep Learning for Optical Communications Reinforcement learning

Reference 15

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Observation d054cee8-d80a-4108-99a1-a012fcc94c10 · outbound

This paper cites Bridging the gap between value and policy based reinforcement learning.

A Survey on Machine and Deep Learning for Optical Communications Bridging the gap between value and policy based reinforcement learning

Reference 16

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This paper cites Deep learning.

A Survey on Machine and Deep Learning for Optical Communications Deep learning

Reference 17

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Observation 6c4834da-b0d1-4a8e-9eb7-d1dbf8613c2f · outbound

This paper cites Evaluating the visualization of what a deep neural network has learnt.

A Survey on Machine and Deep Learning for Optical Communications Evaluating the visualization of what a deep neural network has learnt

Reference 18

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Observation bfae74d5-3054-496b-b75f-04b90d0a232d · outbound

This paper cites Recurrent neural networks. Design and applications.

A Survey on Machine and Deep Learning for Optical Communications Recurrent neural networks. Design and applications

Reference 19

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Observation ac0a1053-cf37-48ea-8d1c-43c23c014d23 · outbound

This paper cites Understanding of a Convolutional Neural Network.

A Survey on Machine and Deep Learning for Optical Communications Understanding of a Convolutional Neural Network

Reference 20

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Observation 44bc6ddf-0f73-4fb3-8c7b-80710f3fa24a · outbound

This paper cites Deep reinforcement learning: A brief survey.

A Survey on Machine and Deep Learning for Optical Communications Deep reinforcement learning: A brief survey

Reference 21

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Observation 56715990-106d-4176-a798-14298ec6f071 · outbound

This paper cites A Tutorial on Machine Learning for Failure Management in Optical Networks.

A Survey on Machine and Deep Learning for Optical Communications A Tutorial on Machine Learning for Failure Management in Optical Networks

Reference 22

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Observation 79275bff-fc3a-46d5-9ecb-8a569962e9e8 · outbound

This paper cites A Survey on Machine Learning Techniques for Routing Optimization in SDN.

A Survey on Machine and Deep Learning for Optical Communications A Survey on Machine Learning Techniques for Routing Optimization in SDN

Reference 23

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Observation b22b77c8-6e68-41ef-836a-c25f71f955a0 · outbound

This paper cites Overview on Routing and Resource Allocation Based Machine Learning in Optical Networks.

A Survey on Machine and Deep Learning for Optical Communications Overview on Routing and Resource Allocation Based Machine Learning in Optical Networks

Reference 24

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Observation 1093ebf2-9f33-4b25-866e-babae6ca6fee · outbound

This paper cites Machine Learning for Network Automation: Overview, Architecture, and Applications [Invited Tutorial].

A Survey on Machine and Deep Learning for Optical Communications Machine Learning for Network Automation: Overview, Architecture, and Applications [Invited Tutorial]

Reference 25

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Observation 8126e1d5-15e8-4232-8bdc-4901bb44f684 · outbound

This paper cites Machine Learning for Intelligent Optical Networks: A Comprehensive Survey.

A Survey on Machine and Deep Learning for Optical Communications Machine Learning for Intelligent Optical Networks: A Comprehensive Survey

Reference 26

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Observation 6786c916-1a31-4e33-b0bd-c0452fe6d446 · outbound

This paper cites Artificial Intelligence (AI) Methods in Optical Networks: A Comprehensive Survey.

A Survey on Machine and Deep Learning for Optical Communications Artificial Intelligence (AI) Methods in Optical Networks: A Comprehensive Survey

Reference 27

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Observation db083210-2f4d-4578-b781-3f122aaa913d · outbound

This paper cites An Overview on Application of Machine Learning Techniques in Optical Networks.

A Survey on Machine and Deep Learning for Optical Communications An Overview on Application of Machine Learning Techniques in Optical Networks

Reference 28

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Observation 61244c8b-8825-4ed4-b903-3e8ca00e8862 · outbound

This paper cites An Optical Communication’s Perspective on Machine Learning and Its Applications.

A Survey on Machine and Deep Learning for Optical Communications An Optical Communication’s Perspective on Machine Learning and Its Applications

Reference 29

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Observation d91d933c-554b-4d82-a8e5-4187961f2158 · outbound

This paper cites A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges.

A Survey on Machine and Deep Learning for Optical Communications A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges

Reference 30

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Observation 16252ebd-a14b-40d8-b6d3-b710125af4af · outbound

This paper cites Artificial Intelligence in Optical Communications: From Machine Learning to Deep Learning.

A Survey on Machine and Deep Learning for Optical Communications Artificial Intelligence in Optical Communications: From Machine Learning to Deep Learning

Reference 31

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Observation 5fe2b0c4-8080-4588-94b9-682f9916cc44 · outbound

This paper cites Harnessing Machine Learning for Fiber-Induced Nonlinearity Mitigation in Long-Haul Coherent Optical OFDM.

A Survey on Machine and Deep Learning for Optical Communications Harnessing Machine Learning for Fiber-Induced Nonlinearity Mitigation in Long-Haul Coherent Optical OFDM

Reference 32

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Observation 8119d680-a5c8-468b-ab02-c170dc73bcbe · outbound

This paper cites A Survey on QoT Prediction Using Machine Learning in Optical Networks.

A Survey on Machine and Deep Learning for Optical Communications A Survey on QoT Prediction Using Machine Learning in Optical Networks

Reference 33

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Observation ea24c4a1-f1ad-4b0c-92a1-3ee49a093f05 · outbound

This paper cites Machine Learning-Aided Optical Performance Monitoring Techniques: A Review.

A Survey on Machine and Deep Learning for Optical Communications Machine Learning-Aided Optical Performance Monitoring Techniques: A Review

Reference 34

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Observation 5fc570b9-680c-46ab-8a17-4690c17a3e33 · outbound

This paper cites Nonlinear Decision Boundary Created by a Machine Learning-Based Classifier to Mitigate Nonlinear Phase Noise.

A Survey on Machine and Deep Learning for Optical Communications Nonlinear Decision Boundary Created by a Machine Learning-Based Classifier to Mitigate Nonlinear Phase Noise

Reference 35

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Observation f8e34479-d411-40e3-a8d4-84b4cf097de9 · outbound

This paper cites An SVM-Based Detection for Coherent Optical APSK Systems with Nonlinear Phase Noise.

A Survey on Machine and Deep Learning for Optical Communications An SVM-Based Detection for Coherent Optical APSK Systems with Nonlinear Phase Noise

Reference 36

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This paper cites Nonparameter Nonlinear Phase Noise Mitigation by Using M-ary Support Vector Machine for Coherent Optical Systems.

A Survey on Machine and Deep Learning for Optical Communications Nonparameter Nonlinear Phase Noise Mitigation by Using M-ary Support Vector Machine for Coherent Optical Systems

Reference 37

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Observation 2f9590f8-3c46-4d55-a231-ce825277681c · outbound

This paper cites Combatting Nonlinear Phase Noise in Coherent Optical Systems with an Optimized Decision Processor Based on Machine Learning.

A Survey on Machine and Deep Learning for Optical Communications Combatting Nonlinear Phase Noise in Coherent Optical Systems with an Optimized Decision Processor Based on Machine Learning

Reference 38

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Observation da43da76-eecf-4486-8084-aa60e258b876 · outbound

This paper cites Machine Learning Assisted Optical Interconnection.

A Survey on Machine and Deep Learning for Optical Communications Machine Learning Assisted Optical Interconnection

Reference 39

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Observation 89d43e9a-f960-45d6-b78c-5022fabccdc4 · outbound

This paper cites Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals.

A Survey on Machine and Deep Learning for Optical Communications Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

Reference 40

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Observation 75c01f3b-7f44-40b8-983d-ec3c2eeac449 · outbound

This paper cites Research of Fiber-Optical Fault Diagnosis Based on Support Vector Machine (SVM) Mining.

A Survey on Machine and Deep Learning for Optical Communications Research of Fiber-Optical Fault Diagnosis Based on Support Vector Machine (SVM) Mining

Reference 41

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Observation 29aa6ab4-9fe7-46bc-9e95-4637e0e47928 · outbound

This paper cites Bit-Based Support Vector Machine Nonlinear Detector for Millimeter-Wave Radio-over-Fiber Mobile Fronthaul Systems.

A Survey on Machine and Deep Learning for Optical Communications Bit-Based Support Vector Machine Nonlinear Detector for Millimeter-Wave Radio-over-Fiber Mobile Fronthaul Systems

Reference 42

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Observation 8c9cbf99-829a-4102-ad09-fcc4af1c2bd2 · outbound

This paper cites Blind Modulation Format Identification Using Decision Tree Twin Support Vector Machine in Optical Communication System.

A Survey on Machine and Deep Learning for Optical Communications Blind Modulation Format Identification Using Decision Tree Twin Support Vector Machine in Optical Communication System

Reference 43

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Observation 54e576a0-4f6b-49c0-91a8-b52b24dfd741 · outbound

This paper cites Equalization Algorithm Based on CMA and SVM for Carrierless Amplitude Phase Modulation in Optical Access Networks.

A Survey on Machine and Deep Learning for Optical Communications Equalization Algorithm Based on CMA and SVM for Carrierless Amplitude Phase Modulation in Optical Access Networks

Reference 44

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Observation ec109644-eb6e-4574-b13d-4b5c1c4d506d · outbound

This paper cites Machine-Learning Detector Based on Support Vector Machine for 122-Gbps Multi-CAP Optical Communication System.

A Survey on Machine and Deep Learning for Optical Communications Machine-Learning Detector Based on Support Vector Machine for 122-Gbps Multi-CAP Optical Communication System

Reference 45

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Observation d6230bcb-f0f4-40c0-9088-6e5a5995e33c · outbound

This paper cites Experimental Study of Support Vector Machine Based Nonlinear Equalizer for VCSEL Based Optical Interconnect.

A Survey on Machine and Deep Learning for Optical Communications Experimental Study of Support Vector Machine Based Nonlinear Equalizer for VCSEL Based Optical Interconnect

Reference 46

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Observation 9cbc7cae-2d68-474d-b6f9-c5d710611260 · outbound

This paper cites QAM Classification Methods by SVM Machine Learning for Improved Optical Interconnection.

A Survey on Machine and Deep Learning for Optical Communications QAM Classification Methods by SVM Machine Learning for Improved Optical Interconnection

Reference 47

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Observation 4f1d9971-2fa5-4f6f-8f83-e1dd33278f65 · outbound

This paper cites Reduction of Nonlinear Intersubcarrier Intermixing in Coherent Optical OFDM by a Fast Newton-Based Support Vector Machine Nonlinear Equalizer.

A Survey on Machine and Deep Learning for Optical Communications Reduction of Nonlinear Intersubcarrier Intermixing in Coherent Optical OFDM by a Fast Newton-Based Support Vector Machine Nonlinear Equalizer

Reference 48

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Observation 7f717950-4956-4def-8345-ae3f56d2b983 · outbound

This paper cites Nonlinear Blind Equalization for 16-QAM Coherent Optical OFDM Using Support Vector Machines.

A Survey on Machine and Deep Learning for Optical Communications Nonlinear Blind Equalization for 16-QAM Coherent Optical OFDM Using Support Vector Machines

Reference 49

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Observation eda49578-4fed-4634-baef-40ba932042ff · outbound

This paper cites Fiber Nonlinearity Equalizer Based on Support Vector Classification for Coherent Optical OFDM.

A Survey on Machine and Deep Learning for Optical Communications Fiber Nonlinearity Equalizer Based on Support Vector Classification for Coherent Optical OFDM

Reference 50

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Observation 94d18e5f-2c35-4186-a107-24b92bc66a46 · outbound

This paper cites Unsupervised Support Vector Machines for Nonlinear Blind Equalization in CO-OFDM.

A Survey on Machine and Deep Learning for Optical Communications Unsupervised Support Vector Machines for Nonlinear Blind Equalization in CO-OFDM

Reference 51

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Observation 5692d51a-1789-4b85-ac9f-743921db93a5 · outbound

This paper cites Fiber Nonlinearity-Induced Penalty Reduction in CO-OFDM by ANN-Based Nonlinear Equalization.

A Survey on Machine and Deep Learning for Optical Communications Fiber Nonlinearity-Induced Penalty Reduction in CO-OFDM by ANN-Based Nonlinear Equalization

Reference 52

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Observation 2cf16f3b-f7bb-40ca-ad41-eb89aa37d7d7 · outbound

This paper cites Traffic Prediction Based on Machine Learning for Elastic Optical Networks.

A Survey on Machine and Deep Learning for Optical Communications Traffic Prediction Based on Machine Learning for Elastic Optical Networks

Reference 53

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Observation afb47d70-3342-4f0d-a79c-56de45bd34aa · outbound

This paper cites Radial Basis Function Neural Network Nonlinear Equalizer for 16-QAM Coherent Optical OFDM.

A Survey on Machine and Deep Learning for Optical Communications Radial Basis Function Neural Network Nonlinear Equalizer for 16-QAM Coherent Optical OFDM

Reference 54

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Observation 1632043f-f7a4-4d4d-b167-b2e416cfd316 · outbound

This paper cites Multi-Layer Perceptron Equalizer for Optical Communication Systems.

A Survey on Machine and Deep Learning for Optical Communications Multi-Layer Perceptron Equalizer for Optical Communication Systems

Reference 55

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Observation 8fd6be0a-859a-401d-a5e5-4abd43482363 · outbound

This paper cites Novel Suboptimal Approaches for Hyperparameter Tuning of Deep Neural Network [Under the Shelf of Optical Communication].

A Survey on Machine and Deep Learning for Optical Communications Novel Suboptimal Approaches for Hyperparameter Tuning of Deep Neural Network [Under the Shelf of Optical Communication]

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.816972Z

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Observation f1ffcfe6-e173-47ce-a3be-b337437e6c25 · outbound

This paper cites Fibre Impairment Compensation Using Artificial Neural Network Equalizer for High-Capacity Coherent Optical OFDM Signals.

A Survey on Machine and Deep Learning for Optical Communications Fibre Impairment Compensation Using Artificial Neural Network Equalizer for High-Capacity Coherent Optical OFDM Signals

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.823727Z

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Observation 343eb5c6-56d6-4d39-a11b-17e8c919573c · outbound

This paper cites Artificial Neural Network Nonlinear Equalizer for Coherent Optical OFDM.

A Survey on Machine and Deep Learning for Optical Communications Artificial Neural Network Nonlinear Equalizer for Coherent Optical OFDM

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.834868Z

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Observation a7e19d3d-f5ea-44b0-bea8-40bb522f07de · outbound

This paper cites Self-Adaptive Erbium-Doped Fiber Amplifiers Using Machine Learning.

A Survey on Machine and Deep Learning for Optical Communications Self-Adaptive Erbium-Doped Fiber Amplifiers Using Machine Learning

Reference 59

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Observation fb02be71-a749-4c9e-bfbd-bc558c6f80d8 · outbound

This paper cites K-Nearest Neighbor Detector for Enhancing Performance of Optical Phase Conjugation System in the Presence of Nonlinear Phase Noise.

A Survey on Machine and Deep Learning for Optical Communications K-Nearest Neighbor Detector for Enhancing Performance of Optical Phase Conjugation System in the Presence of Nonlinear Phase Noise

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.856418Z

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Observation f96793b3-955f-4d3d-951f-51eb37616716 · outbound

This paper cites Nonlinearity Mitigation Using a Machine Learning Detector Based on k-Nearest Neighbors.

A Survey on Machine and Deep Learning for Optical Communications Nonlinearity Mitigation Using a Machine Learning Detector Based on k-Nearest Neighbors

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.865977Z

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Observation 25c3d9db-3712-4095-84ca-21b4444f30d1 · outbound

This paper cites Non-data-aided k-nearest neighbors technique for optical fiber nonlinearity mitigation.

A Survey on Machine and Deep Learning for Optical Communications Non-data-aided k-nearest neighbors technique for optical fiber nonlinearity mitigation

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.874168Z

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Observation a07e1a2f-0222-4e81-96cd-25b70961b652 · outbound

This paper cites Sparse identification for nonlinear optical communication systems: SINO method.

A Survey on Machine and Deep Learning for Optical Communications Sparse identification for nonlinear optical communication systems: SINO method

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.879976Z

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Observation 9649195c-7131-4c34-8b46-ecff1f40b867 · outbound

This paper cites Sparse identification for nonlinear optical communication systems.

A Survey on Machine and Deep Learning for Optical Communications Sparse identification for nonlinear optical communication systems

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.886261Z

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Observation 192d4a5f-77ae-4c8d-b3ab-a8372310360f · outbound

This paper cites Fractionally spaced clustering based equalizer for optical channels.

A Survey on Machine and Deep Learning for Optical Communications Fractionally spaced clustering based equalizer for optical channels

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.893054Z

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Observation af024140-f00c-4ec8-a4ac-4d54ecae27fe · outbound

This paper cites Blind nonlinearity equalization by machine-learning-based clustering for single-and multi-channel coherent optical OFDM.

A Survey on Machine and Deep Learning for Optical Communications Blind nonlinearity equalization by machine-learning-based clustering for single-and multi-channel coherent optical OFDM

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.899159Z

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Observation 69bf1d1a-768f-45ea-ba9b-919057575eb7 · outbound

This paper cites Mitigation of time-varying distortions in Nyquist-WDM systems using machine learning.

A Survey on Machine and Deep Learning for Optical Communications Mitigation of time-varying distortions in Nyquist-WDM systems using machine learning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.905440Z

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Observation 04b8bdde-baad-4b29-925e-b18a1a47180c · outbound

This paper cites DBSCAN for nonlinear equalization in high-capacity multi-carrier optical communications.

A Survey on Machine and Deep Learning for Optical Communications DBSCAN for nonlinear equalization in high-capacity multi-carrier optical communications

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:58:44.642378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 943b07da-fed3-40b8-b4f4-70b5d74b3579 · outbound

This paper cites A Machine Learning-Based Detection Technique for Optical Fiber Nonlinearity Mitigation.

A Survey on Machine and Deep Learning for Optical Communications A Machine Learning-Based Detection Technique for Optical Fiber Nonlinearity Mitigation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.920911Z

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Observation b29a54c6-32bf-42ca-9561-c4254a4a0db4 · outbound

This paper cites K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system.

A Survey on Machine and Deep Learning for Optical Communications K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.931276Z

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Observation dc9c871f-62ba-4b0d-9e2c-92ed886b8506 · outbound

This paper cites Spectrally efficient digitized radio-over-fiber system with K-means clustering-based multi-dimensional quantization.

A Survey on Machine and Deep Learning for Optical Communications Spectrally efficient digitized radio-over-fiber system with K-means clustering-based multi-dimensional quantization

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.937698Z

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Observation cf601eae-2682-4bf3-a944-7773eb54f765 · outbound

This paper cites Optical phase-modulated radio-over-fiber links with K-means algorithm for digital demodulation of 8PSK subcarrier multiplexed signals.

A Survey on Machine and Deep Learning for Optical Communications Optical phase-modulated radio-over-fiber links with K-means algorithm for digital demodulation of 8PSK subcarrier multiplexed signals

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.944106Z

Source-reported events for the cited work

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Observation 8282fbce-298b-4832-81e9-28a41fbe0dd0 · outbound

This paper cites Experimental 2.5-Gb/s QPSK WDM Phase-Modulated Radio-Over-Fiber Link With Digital Demodulation by a K-Means Algorithm.

A Survey on Machine and Deep Learning for Optical Communications Experimental 2.5-Gb/s QPSK WDM Phase-Modulated Radio-Over-Fiber Link With Digital Demodulation by a K-Means Algorithm

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.954804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 247999f7-d5e1-41ed-83e9-2b3ab583536e · outbound

This paper cites Application of machine learning techniques for amplitude and phase noise characterization.

A Survey on Machine and Deep Learning for Optical Communications Application of machine learning techniques for amplitude and phase noise characterization

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.961786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 663c568c-c174-448b-b611-359c16ce337c · outbound

This paper cites Machine learning techniques in optical communication.

A Survey on Machine and Deep Learning for Optical Communications Machine learning techniques in optical communication

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.968449Z

Source-reported events for the cited work

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Observation e36559fa-056b-47a8-aa7a-6c0ddfae9aeb · outbound

This paper cites Optical Nonlinear Phase Noise Compensation for 9 × 32-Gbaud PolDM-16 QAM Transmission Using a Code-Aided Expectation-Maximization Algorithm.

A Survey on Machine and Deep Learning for Optical Communications Optical Nonlinear Phase Noise Compensation for 9 × 32-Gbaud PolDM-16 QAM Transmission Using a Code-Aided Expectation-Maximization Algorithm

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.975206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deb723de-a1c7-47b3-a375-8786bcd1b2c2 · outbound

This paper cites Blind equalization in optical communications using independent component analysis.

A Survey on Machine and Deep Learning for Optical Communications Blind equalization in optical communications using independent component analysis

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.986557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fc83ddf-ee95-4e5f-ade6-f4190e5ddbdd · outbound

This paper cites Polarization demultiplexing based on independent component analysis in optical coherent receivers.

A Survey on Machine and Deep Learning for Optical Communications Polarization demultiplexing based on independent component analysis in optical coherent receivers

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:42.994802Z

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Observation ec3b988f-2c99-4e73-9d19-ca62d4754272 · outbound

This paper cites Channel equalization in optical OFDM systems using independent component analysis.

A Survey on Machine and Deep Learning for Optical Communications Channel equalization in optical OFDM systems using independent component analysis

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.000999Z

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Unavailable: canonical work link unavailable.

Observation 3727e33b-268a-450e-8326-e6bec07fdac6 · outbound

This paper cites Deep learning for interference cancellation in non-orthogonal signal based optical communication systems.

A Survey on Machine and Deep Learning for Optical Communications Deep learning for interference cancellation in non-orthogonal signal based optical communication systems

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.008281Z

Source-reported events for the cited work

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Observation 67bb6ff6-ef29-497a-a00e-e08037a9bddf · outbound

This paper cites Exceeding the Nonlinear Shannon-Limit in Coherent Optical Communications by MIMO Machine Learning.

A Survey on Machine and Deep Learning for Optical Communications Exceeding the Nonlinear Shannon-Limit in Coherent Optical Communications by MIMO Machine Learning

Reference 81

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:58:44.611388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 49bf59c7-f1f9-45b6-b554-b7a05e426c66 · outbound

This paper cites Nonlinear interference mitigation via deep neural networks.

A Survey on Machine and Deep Learning for Optical Communications Nonlinear interference mitigation via deep neural networks

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.023463Z

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Observation 2cd09729-2b85-4468-8959-629da1a008cc · outbound

This paper cites MIMO detection using a deep learning neural network in a mode division multiplexing optical transmission system.

A Survey on Machine and Deep Learning for Optical Communications MIMO detection using a deep learning neural network in a mode division multiplexing optical transmission system

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.034270Z

Source-reported events for the cited work

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Observation 16e5d039-f591-4365-babb-ed40482c0890 · outbound

This paper cites End-to-end deep learning of optical fiber communications.

A Survey on Machine and Deep Learning for Optical Communications End-to-end deep learning of optical fiber communications

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.041167Z

Source-reported events for the cited work

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Observation 7e809024-b87c-4b49-a320-f688ea81a74c · outbound

This paper cites Machine learning-based Raman amplifier design.

A Survey on Machine and Deep Learning for Optical Communications Machine learning-based Raman amplifier design

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.048835Z

Source-reported events for the cited work

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Observation 851d90be-fef7-40af-9545-a442d6f0138c · outbound

This paper cites End-to-end deep learning for joint geometric-probabilistic constellation shaping in FMF system.

A Survey on Machine and Deep Learning for Optical Communications End-to-end deep learning for joint geometric-probabilistic constellation shaping in FMF system

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.055647Z

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Observation fa50c546-4eb7-4a46-9953-7660261051dd · outbound

This paper cites End-to-End Optimized Transmission over Dispersive Intensity-Modulated Channels Using Bidirectional Recurrent Neural Networks.

A Survey on Machine and Deep Learning for Optical Communications End-to-End Optimized Transmission over Dispersive Intensity-Modulated Channels Using Bidirectional Recurrent Neural Networks

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.066138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3f0bd47-4e00-430d-9e2b-3c0c0925112e · outbound

This paper cites An introduction to deep learning for the physical layer.

A Survey on Machine and Deep Learning for Optical Communications An introduction to deep learning for the physical layer

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.073577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 333b4a8a-ecf8-4c25-b4b0-c21d765ea057 · outbound

This paper cites Deep learning of geometric constellation shaping including fiber nonlinearities.

A Survey on Machine and Deep Learning for Optical Communications Deep learning of geometric constellation shaping including fiber nonlinearities

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.080301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73d55d17-3360-4dc4-807d-d323f9d468f5 · outbound

This paper cites Achievable information rates for nonlinear fiber communication via end-to-end autoencoder learning.

A Survey on Machine and Deep Learning for Optical Communications Achievable information rates for nonlinear fiber communication via end-to-end autoencoder learning

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.088971Z

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Unavailable: canonical work link unavailable.

Observation 7cbdc083-8aea-4346-9289-92d094151358 · outbound

This paper cites Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning.

A Survey on Machine and Deep Learning for Optical Communications Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning

Reference 91

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:58:44.582953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b1ca697c-70fa-4b3a-9ae5-4b5aafabefda · outbound

This paper cites Low Computationally Complex Recurrent Neural Network for High Speed Optical Fiber Transmission.

A Survey on Machine and Deep Learning for Optical Communications Low Computationally Complex Recurrent Neural Network for High Speed Optical Fiber Transmission

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.101455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e50a070a-dd45-4d4d-9460-ba6d3a07d759 · outbound

This paper cites Cascade Recurrent Neural Network Enabled 100-Gb/s PAM4 Short-Reach Optical Link Based on DML.

A Survey on Machine and Deep Learning for Optical Communications Cascade Recurrent Neural Network Enabled 100-Gb/s PAM4 Short-Reach Optical Link Based on DML

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.106933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dda00aa3-acc6-4827-8590-4d7c5c6bae5b · outbound

This paper cites Cascade Recurrent Neural Network-Assisted Nonlinear Equalization for a 100 Gb/s PAM4 Short-Reach Direct Detection System.

A Survey on Machine and Deep Learning for Optical Communications Cascade Recurrent Neural Network-Assisted Nonlinear Equalization for a 100 Gb/s PAM4 Short-Reach Direct Detection System

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.111642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cf8c516-2a67-41d2-b32d-45b0ee73b07b · outbound

This paper cites Efficient Deep Learning of Nonlinear Fiber-Optic Communications Using a Convolutional Recurrent Neural Network.

A Survey on Machine and Deep Learning for Optical Communications Efficient Deep Learning of Nonlinear Fiber-Optic Communications Using a Convolutional Recurrent Neural Network

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.119151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2df02a7-c6f7-4f80-93b1-a038484240dc · outbound

This paper cites Joint Equalization of Linear and Nonlinear Impairments for PAM4 Short-Reach Direct Detection Systems.

A Survey on Machine and Deep Learning for Optical Communications Joint Equalization of Linear and Nonlinear Impairments for PAM4 Short-Reach Direct Detection Systems

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.126802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0419195-5fab-4e23-a438-2012d1e274b3 · outbound

This paper cites Feedforward and Recurrent Neural Network-Based Transfer Learning for Nonlinear Equalization in Short-Reach Optical Links.

A Survey on Machine and Deep Learning for Optical Communications Feedforward and Recurrent Neural Network-Based Transfer Learning for Nonlinear Equalization in Short-Reach Optical Links

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.133873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7c740ab-c0e7-403a-b2f8-fc8d6159fe3c · outbound

This paper cites Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications.

A Survey on Machine and Deep Learning for Optical Communications Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.140956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed84ed4-e69b-44ea-a960-95ab3531df9d · outbound

This paper cites Optical Fiber Communication Systems Based on End-to-End Deep Learning.

A Survey on Machine and Deep Learning for Optical Communications Optical Fiber Communication Systems Based on End-to-End Deep Learning

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.146600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fce07ea1-e291-47fb-82be-ff9372467a12 · outbound

This paper cites Performance and Complexity Analysis of Bi-Directional Recurrent Neural Network Models Versus V olterra Nonlinear Equalizers in Digital Coherent Systems.

A Survey on Machine and Deep Learning for Optical Communications Performance and Complexity Analysis of Bi-Directional Recurrent Neural Network Models Versus V olterra Nonlinear Equalizers in Digital Coherent Systems

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-11T18:58:43.153402Z

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