Efficient training and design of photonic neural network through neuroevolution | Paper Citation Record

Observation 95b75faf-3bf6-4867-9bae-b5ad52dc8c48 · outbound

This paper cites an unresolved cited work.

Efficient training and design of photonic neural network through neuroevolution Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:18:35.614425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c3bea58a-a3b2-48e1-867c-431d37768cf4 · outbound

This paper cites 1(a), the network architecture of ANNs imitates the structure of biological neural network which includes a great number of neuron s and connections layer by layer [1].

Efficient training and design of photonic neural network through neuroevolution 1(a), the network architecture of ANNs imitates the structure of biological neural network which includes a great number of neuron s and connections layer by layer [1]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.517584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bd2cef27-e434-4cba-94c2-8fac35ebc68f · outbound

This paper cites The iris plants dataset is a simple dataset which includes 150 instances (4 attributes for each instance).

Efficient training and design of photonic neural network through neuroevolution The iris plants dataset is a simple dataset which includes 150 instances (4 attributes for each instance)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.423771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 58c4aa93-e642-4da9-abf8-3e32e03349ef · outbound

This paper cites Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups,.

Efficient training and design of photonic neural network through neuroevolution Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.172438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9c69d559-b81e-4e55-ac93-77f061e80635 · outbound

This paper cites A review of unsupervised feature learning and deep learning for time-series modeling,.

Efficient training and design of photonic neural network through neuroevolution A review of unsupervised feature learning and deep learning for time-series modeling,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.045800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a6da2eb3-3948-4030-8e8c-fed1adf95f79 · outbound

This paper cites Deep learning,.

Efficient training and design of photonic neural network through neuroevolution Deep learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.238781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cd0f4ab5-29b5-4d49-add1-d3c0c09a71e8 · outbound

This paper cites Deep learning in neural networks: An overview,.

Efficient training and design of photonic neural network through neuroevolution Deep learning in neural networks: An overview,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.209652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c2aa1a5-ecff-47a3-a4ea-e884d6f78eb7 · outbound

This paper cites Recent trends in deep learning based natural language processing,.

Efficient training and design of photonic neural network through neuroevolution Recent trends in deep learning based natural language processing,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.189012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 39ca90b8-1586-4907-85ea-5d39db6145d5 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Efficient training and design of photonic neural network through neuroevolution Imagenet classification with deep convolutional neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.007045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f9db6a92-5b2b-4205-8b9c-4e2867e530be · outbound

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

Efficient training and design of photonic neural network through neuroevolution Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T15:18:32.089480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85526f3c-7b13-40e0-b3fe-00fb4f7b9c9b · outbound

This paper cites End to End Learning for Self-Driving Cars.

Efficient training and design of photonic neural network through neuroevolution End to End Learning for Self-Driving Cars

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T15:18:32.029751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0631bb5-4ea1-465c-bb48-3def7c936a09 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Efficient training and design of photonic neural network through neuroevolution Playing Atari with Deep Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T15:18:32.071890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a6baef6-fcb5-46bb-b7e6-e766376bf99a · outbound

This paper cites Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates,.

Efficient training and design of photonic neural network through neuroevolution Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.027718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 265ee624-5aaf-4050-80bb-065aeac8fa20 · outbound

This paper cites Theano: Deep learning on gpus with python,.

Efficient training and design of photonic neural network through neuroevolution Theano: Deep learning on gpus with python,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.772114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 608d2811-96cd-461e-b66d-c2f74f73c1a9 · outbound

This paper cites Optimizing fpga-based accelerator design for deep convolutional neural networks,.

Efficient training and design of photonic neural network through neuroevolution Optimizing fpga-based accelerator design for deep convolutional neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.750199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 06d070c9-6272-4c8f-8843-a7f1f713cb0f · outbound

This paper cites Going deeper with convolutions,.

Efficient training and design of photonic neural network through neuroevolution Going deeper with convolutions,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.928486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9ba0ecc2-f50a-4ab3-bd66-f54f55d16464 · outbound

This paper cites Deep residual learning for image recognition,.

Efficient training and design of photonic neural network through neuroevolution Deep residual learning for image recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.809447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d7e91874-dfc5-4585-8599-2bb4dd0c91be · outbound

This paper cites Long short-term memory,.

Efficient training and design of photonic neural network through neuroevolution Long short-term memory,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.791191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b57bc999-9c0f-4c69-bed1-a412d02b27ad · outbound

This paper cites The spinnaker project,.

Efficient training and design of photonic neural network through neuroevolution The spinnaker project,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.492410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b52633d4-e573-4d7f-bc96-83376b6930ef · outbound

This paper cites A CMOS Spiking Neuron for Brain-Inspired Neural Networks With Resistive Synapses andIn SituLearning,.

Efficient training and design of photonic neural network through neuroevolution A CMOS Spiking Neuron for Brain-Inspired Neural Networks With Resistive Synapses andIn SituLearning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.474232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d3e716c1-4837-465f-9872-56ac165de11e · outbound

This paper cites Diannao: A small-footprint high- throughput accelerator for ubiquitous machine-learning,.

Efficient training and design of photonic neural network through neuroevolution Diannao: A small-footprint high- throughput accelerator for ubiquitous machine-learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.683602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6cb3c81b-c44f-4d8d-ae44-e3bbf8729067 · outbound

This paper cites Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,.

Efficient training and design of photonic neural network through neuroevolution Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.598376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d22df329-7559-47dc-8e93-9ec6121bb8c6 · outbound

This paper cites Loihi: A neuromorphic manycore processor with on-chip learning,.

Efficient training and design of photonic neural network through neuroevolution Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.517653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ba66d5d7-0807-439b-bb0d-7038e24964d4 · outbound

This paper cites Recent progress in semiconductor excitable lasers for photonic spike processing,.

Efficient training and design of photonic neural network through neuroevolution Recent progress in semiconductor excitable lasers for photonic spike processing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.321879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 132979cf-6321-47f8-85b1-f842e3d7a411 · outbound

This paper cites As alternative approaches to gradient - based methods, evolutionary algorithms are representative gradient free methods to optimize the weights of ANNs [41, 42].

Efficient training and design of photonic neural network through neuroevolution As alternative approaches to gradient - based methods, evolutionary algorithms are representative gradient free methods to optimize the weights of ANNs [41, 42]

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.441607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3849ce6c-bd17-44f6-bcea-48f8a7b5d120 · outbound

This paper cites Optical computing,.

Efficient training and design of photonic neural network through neuroevolution Optical computing,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.425254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 48a425fd-a8c9-428b-b4c3-fb2471ef2cb7 · outbound

This paper cites A leaky integrate-and-fire laser neuron for ultrafast cognitive computing,.

Efficient training and design of photonic neural network through neuroevolution A leaky integrate-and-fire laser neuron for ultrafast cognitive computing,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.355415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 09cae002-46b8-4f94-ad63-bf6da028ced4 · outbound

This paper cites Multi-channel control for microring weight banks,.

Efficient training and design of photonic neural network through neuroevolution Multi-channel control for microring weight banks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.338527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 150ef774-2d0c-468b-8682-9474d51befdf · outbound

This paper cites Variance preserving initialization for training deep neuromorphic photonic networks with sinusoidal activations,.

Efficient training and design of photonic neural network through neuroevolution Variance preserving initialization for training deep neuromorphic photonic networks with sinusoidal activations,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.207208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d9c9df27-6cb5-4758-a7b2-93b6ee037145 · outbound

This paper cites Deep learning with coherent nanophotonic circuits,.

Efficient training and design of photonic neural network through neuroevolution Deep learning with coherent nanophotonic circuits,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.301027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1f9a2dab-8ec0-4efb-8112-2255bfe8d1ff · outbound

This paper cites On-Chip Optical Convolutional Neural Networks.

Efficient training and design of photonic neural network through neuroevolution On-Chip Optical Convolutional Neural Networks

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-14T15:18:33.052088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dfe9c7d8-ffd8-44ff-af0a-f2de43544134 · outbound

This paper cites Reinforcement learning in a large-scale photonic recurrent neural network,.

Efficient training and design of photonic neural network through neuroevolution Reinforcement learning in a large-scale photonic recurrent neural network,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.252188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f1d62a7-6a3b-4afd-aab7-6974f40dbbe4 · outbound

This paper cites All-optical machine learning using diffractive deep neural networks,.

Efficient training and design of photonic neural network through neuroevolution All-optical machine learning using diffractive deep neural networks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.223695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e82ada52-b085-4949-af81-72310d6a6c98 · outbound

This paper cites Inverse design in nanophotonics,.

Efficient training and design of photonic neural network through neuroevolution Inverse design in nanophotonics,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.050647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 58da6789-6d6b-4fcc-9713-18f0639cc32d · outbound

This paper cites An all-optical neuron with sigmoid activation function,.

Efficient training and design of photonic neural network through neuroevolution An all-optical neuron with sigmoid activation function,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.187985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 94066fb3-c7d3-49ec-9d47-c4074f944fb3 · outbound

This paper cites Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks.

Efficient training and design of photonic neural network through neuroevolution Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-14T15:18:32.977096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation db4ce5b6-f273-4450-bdf4-4a152e1383b2 · outbound

This paper cites Self-learning photonic signal processor with an optical neural network chip.

Efficient training and design of photonic neural network through neuroevolution Self-learning photonic signal processor with an optical neural network chip

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-14T15:18:32.877029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 543c7cd2-6460-416e-a62a-4132b71a2b94 · outbound

This paper cites Training of photonic neural networks through in situ backpropagation and gradient measurement,.

Efficient training and design of photonic neural network through neuroevolution Training of photonic neural networks through in situ backpropagation and gradient measurement,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.099992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f664fba2-5325-493d-8bf3-6ec0fdbbdaee · outbound

This paper cites Binary particle swarm optimized 2× 2 power splitters in a standard foundry silicon photonic platform,.

Efficient training and design of photonic neural network through neuroevolution Binary particle swarm optimized 2× 2 power splitters in a standard foundry silicon photonic platform,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.849709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c0adaa8-07d9-4ed4-a550-fee3d1855686 · outbound

This paper cites Silicon photonics circuit design: methods, tools and challenges,.

Efficient training and design of photonic neural network through neuroevolution Silicon photonics circuit design: methods, tools and challenges,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.033599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54fc0694-b7b2-43f0-9e82-fad8d0ac3e27 · outbound

This paper cites Efficient spectrum prediction and inverse design for plasmonic waveguide systems based on artificial neural networks,.

Efficient training and design of photonic neural network through neuroevolution Efficient spectrum prediction and inverse design for plasmonic waveguide systems based on artificial neural networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:34.015893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 19b00263-0f0c-4278-90bd-de1fbfe67550 · outbound

This paper cites Genetically optimized on-chip wideband ultracompact reflectors and Fabry–Perot cavities,.

Efficient training and design of photonic neural network through neuroevolution Genetically optimized on-chip wideband ultracompact reflectors and Fabry–Perot cavities,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.930986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6ae58990-01a9-4d5f-99aa-42f428274b30 · outbound

This paper cites Optimization for Gold Nanostructure-Based Surface Plasmon Biosensors Using a Microgenetic Algorithm,.

Efficient training and design of photonic neural network through neuroevolution Optimization for Gold Nanostructure-Based Surface Plasmon Biosensors Using a Microgenetic Algorithm,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.911140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7e29ae8-ff7b-4d28-a341-7de885050321 · outbound

This paper cites Spiking neural networks for handwritten digit recognition—Supervised learning and network optimization,.

Efficient training and design of photonic neural network through neuroevolution Spiking neural networks for handwritten digit recognition—Supervised learning and network optimization,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.648766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 29df41c5-cd23-4663-b941-231e318f9817 · outbound

This paper cites Designing neural networks through neuroevolution,.

Efficient training and design of photonic neural network through neuroevolution Designing neural networks through neuroevolution,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.696741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d90b5b6c-1a1e-4417-bb4a-57be99934546 · outbound

This paper cites Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning.

Efficient training and design of photonic neural network through neuroevolution Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-14T15:18:32.680745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e010bd0a-397e-4143-882d-f8dab4fe4135 · outbound

This paper cites Rainbow: Combining improvements in deep reinforcement learning,.

Efficient training and design of photonic neural network through neuroevolution Rainbow: Combining improvements in deep reinforcement learning,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.681142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e682819d-10cf-4b0b-a415-71b1659bff0e · outbound

This paper cites Deep learning in spiking neural networks,.

Efficient training and design of photonic neural network through neuroevolution Deep learning in spiking neural networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.663690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 01bd2eae-8870-4841-afc5-4edc804ced8b · outbound

This paper cites Optimal design for universal multiport interferometers,.

Efficient training and design of photonic neural network through neuroevolution Optimal design for universal multiport interferometers,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.486003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aec82912-6503-4f68-ba56-a57377c72616 · outbound

This paper cites Deep learning with spiking neurons: opportunities and challenges,.

Efficient training and design of photonic neural network through neuroevolution Deep learning with spiking neurons: opportunities and challenges,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.620164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d71763a7-644f-4d2f-be09-91496a4b48c8 · outbound

This paper cites Nonlinear optics with 2D layered materials,.

Efficient training and design of photonic neural network through neuroevolution Nonlinear optics with 2D layered materials,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.530422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a6ea8bfb-bdf0-4a9b-b3ef-f7ad6f60fa56 · outbound

This paper cites an unresolved cited work.

Efficient training and design of photonic neural network through neuroevolution Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:18:33.515798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7105fc2-4102-4a2f-8efd-408fcced2760 · outbound

This paper cites Experimental realization of any discrete unitary operator,.

Efficient training and design of photonic neural network through neuroevolution Experimental realization of any discrete unitary operator,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.501124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1af3c7b9-6b17-4413-975a-2bdbb81dc885 · outbound

This paper cites Feature selection based on hybridization of genetic algorithm and particle swarm optimization,.

Efficient training and design of photonic neural network through neuroevolution Feature selection based on hybridization of genetic algorithm and particle swarm optimization,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.413189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f6412510-a0e9-4838-86fa-4fcaeefe74f9 · outbound

This paper cites A study of cross-validation and bootstrap for accuracy estimation and model selection,.

Efficient training and design of photonic neural network through neuroevolution A study of cross-validation and bootstrap for accuracy estimation and model selection,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.292923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8ffa95ed-783e-4a33-b21e-d74cfd7f0f0c · outbound

This paper cites Maximum certainty data partitioning,.

Efficient training and design of photonic neural network through neuroevolution Maximum certainty data partitioning,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.274424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55724615-dce7-41c3-8ded-d4506ac55b40 · outbound

This paper cites Automatic identification of digital modulation types,.

Efficient training and design of photonic neural network through neuroevolution Automatic identification of digital modulation types,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:33.188249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 03b55f23-aba8-4f9d-bf7e-624aabd1ad01 · outbound

This paper cites This phenomenon is easy to explain because the large populations enhance the global searching ability of the evolution algorithms [36].

Efficient training and design of photonic neural network through neuroevolution This phenomenon is easy to explain because the large populations enhance the global searching ability of the evolution algorithms [36]

Reference 200

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:18:35.383292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers