Machine Intelligence on Wireless Edge Networks | Paper Citation Record

Observation e1f9acad-cc37-47c3-9dd5-0d338a825c6d · outbound

This paper cites Efficient processing of deep neural networks: A tutorial and survey.

Machine Intelligence on Wireless Edge Networks Efficient processing of deep neural networks: A tutorial and survey

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.376017Z

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Observation cfb7f3b5-a6d2-4441-9e93-f55933096f66 · outbound

This paper cites Computing’s energy problem (and what we can do about it).

Machine Intelligence on Wireless Edge Networks Computing’s energy problem (and what we can do about it)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.364661Z

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Observation 3b09e82d-2fc2-43fd-830f-ea0a15b08a8e · outbound

This paper cites In-datacenter per- formance analysis of a tensor processing unit.

Machine Intelligence on Wireless Edge Networks In-datacenter per- formance analysis of a tensor processing unit

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.354518Z

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Observation 17026e21-f437-4652-bc5e-4381da86e1c5 · outbound

This paper cites The emergence of edge computing.

Machine Intelligence on Wireless Edge Networks The emergence of edge computing

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.343883Z

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Observation d77e2563-a226-4b8d-9177-5b13e7699253 · outbound

This paper cites A method to estimate the energy consumption of deep neu- ral networks.

Machine Intelligence on Wireless Edge Networks A method to estimate the energy consumption of deep neu- ral networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.333433Z

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Observation b77e87c0-3ba0-4905-b674-5dee9941da05 · outbound

This paper cites Split learning for health: Distributed deep learning without sharing raw patient data.

Machine Intelligence on Wireless Edge Networks Split learning for health: Distributed deep learning without sharing raw patient data

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:22.963609Z

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Observation e18bbb3a-384b-402a-bf88-61a8b112a1cb · outbound

This paper cites Multi-key privacy-preserving deep learning in cloud computing.

Machine Intelligence on Wireless Edge Networks Multi-key privacy-preserving deep learning in cloud computing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.322750Z

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Observation 164b3faa-d299-4a61-8488-7c21bb384e3c · outbound

This paper cites Quantum-secure multi- party deep learning.

Machine Intelligence on Wireless Edge Networks Quantum-secure multi- party deep learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:23.083418Z

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Observation 481c50ac-ffa8-4261-a388-fdc5e8e9575b · outbound

This paper cites Wright, Peter L.

Machine Intelligence on Wireless Edge Networks Wright, Peter L

Reference 9

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Observation 42a5bba5-1f30-445c-ae31-c26582090cc5 · outbound

This paper cites Backpropagation-free train- ing of deep physical neural networks.

Machine Intelligence on Wireless Edge Networks Backpropagation-free train- ing of deep physical neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.305432Z

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Observation d85c1b95-7cc8-4e0c-87bb-f8db581025c0 · outbound

This paper cites Deep physical neural networks trained with backpropagation.

Machine Intelligence on Wireless Edge Networks Deep physical neural networks trained with backpropagation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:23.276781Z

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Observation 28ae8c3a-c2e2-4617-a515-53e07b987723 · outbound

This paper cites Inference in artificial intelligence with deep optics and photonics.

Machine Intelligence on Wireless Edge Networks Inference in artificial intelligence with deep optics and photonics

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.287805Z

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Observation 045869dd-f08d-426b-8be0-6df63a3df79b · outbound

This paper cites Memory devices and applications for in-memory computing.

Machine Intelligence on Wireless Edge Networks Memory devices and applications for in-memory computing

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.277551Z

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Observation 63c6cce6-75d2-4093-8dbc-9bbef0e8f77b · outbound

This paper cites Photonics for artificial intelligence and neuro- morphic computing.

Machine Intelligence on Wireless Edge Networks Photonics for artificial intelligence and neuro- morphic computing

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.267204Z

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Observation 83e27fb6-e2c5-470d-802e-1e9d8c0c94bf · outbound

This paper cites Fully forward mode training for optical neural networks.

Machine Intelligence on Wireless Edge Networks Fully forward mode training for optical neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.256799Z

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Observation bc2c192c-8414-491a-99cb-4912882123ca · outbound

This paper cites Nonlinear processing with lin- ear optics.

Machine Intelligence on Wireless Edge Networks Nonlinear processing with lin- ear optics

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.246775Z

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Observation 88bf81bf-1a49-4d76-a16e-d1ee4a2a4f6f · outbound

This paper cites The physics of optical computing.

Machine Intelligence on Wireless Edge Networks The physics of optical computing

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:23.670683Z

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Unavailable: canonical work link unavailable.

Observation 46fac8e6-3201-4dde-9dd5-7eb2c91c40d0 · outbound

This paper cites An on-chip photonic deep neural network for image classifica- tion.

Machine Intelligence on Wireless Edge Networks An on-chip photonic deep neural network for image classifica- tion

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.229311Z

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Observation 56db5db3-37c0-4cc5-be06-b7e2af1716e0 · outbound

This paper cites Parallel convolutional processing using an integrated photonic tensor core.

Machine Intelligence on Wireless Edge Networks Parallel convolutional processing using an integrated photonic tensor core

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.219066Z

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Observation aedad37c-f50d-44ef-893c-fc5422f632a1 · outbound

This paper cites Deep learning with coherent vcsel neural networks.

Machine Intelligence on Wireless Edge Networks Deep learning with coherent vcsel neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.209535Z

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Observation 36c38793-7dc1-4f5a-8d65-cb63c8a158ee · outbound

This paper cites An optical neural network using less than 1 photon per multiplication.

Machine Intelligence on Wireless Edge Networks An optical neural network using less than 1 photon per multiplication

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.200014Z

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Observation 48315775-2a58-4a7e-be22-c161cac52c92 · outbound

This paper cites 11 tops photonic convolutional accelerator for optical neural networks.

Machine Intelligence on Wireless Edge Networks 11 tops photonic convolutional accelerator for optical neural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.190127Z

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Observation e7cad960-364d-4393-814a-ecc22c489763 · outbound

This paper cites Programmable photonic circuits.

Machine Intelligence on Wireless Edge Networks Programmable photonic circuits

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.180012Z

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Observation 05ffdacd-0318-4973-b739-fe673e29f5a2 · outbound

This paper cites A three- terminal nanophotonic integrator for deep neural networks.

Machine Intelligence on Wireless Edge Networks A three- terminal nanophotonic integrator for deep neural networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.170034Z

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Observation 0b644ee3-f9f6-4958-9509-771b0a5648ef · outbound

This paper cites QAMNet: Fast and Efficient Optical QAM Neural Networks.

Machine Intelligence on Wireless Edge Networks QAMNet: Fast and Efficient Optical QAM Neural Networks

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:07:27.513150Z

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

Observation 5e46ff03-42e9-4fa6-a2c8-84bb940da7c0 · outbound

This paper cites Attojoule optoelectronics for low-energy information processing and communications.

Machine Intelligence on Wireless Edge Networks Attojoule optoelectronics for low-energy information processing and communications

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.159866Z

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Observation c3cd2d3c-a271-4745-89cc-9851d9464169 · outbound

This paper cites Analog optical computer for ai inference and com- binatorial optimization.

Machine Intelligence on Wireless Edge Networks Analog optical computer for ai inference and com- binatorial optimization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.149497Z

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Observation 6dde5f69-6efe-47b8-a5a8-e93658f0fc60 · outbound

This paper cites Large-scale photonic chiplet taichi empowers 160-tops/w artificial general intelligence.

Machine Intelligence on Wireless Edge Networks Large-scale photonic chiplet taichi empowers 160-tops/w artificial general intelligence

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.138854Z

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Observation d2ba3811-ca3a-4e8f-a4fe-f18c53d93509 · outbound

This paper cites All-optical ma- chine learning using diffractive deep neural networks.

Machine Intelligence on Wireless Edge Networks All-optical ma- chine learning using diffractive deep neural networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.130015Z

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

Observation 3b38a61c-aa0a-4d49-8784-eff4c6b4c688 · outbound

This paper cites Isaac: A convolutional neural network accelerator with in-situ analog arithmetic in cross- bars.

Machine Intelligence on Wireless Edge Networks Isaac: A convolutional neural network accelerator with in-situ analog arithmetic in cross- bars

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.120142Z

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Observation 04465b8b-0992-4f0e-b631-9637c769a6c9 · outbound

This paper cites Prime: A novel processing-in-memory architecture for neural network compu- tation in reram-based main memory.

Machine Intelligence on Wireless Edge Networks Prime: A novel processing-in-memory architecture for neural network compu- tation in reram-based main memory

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.109881Z

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

Observation 9b2bcb70-9e16-4bf4-b2a9-7acebbd3d79e · outbound

This paper cites PUMA: A programmable ultra-efficient memristor-based accelerator for machine learning inference.

Machine Intelligence on Wireless Edge Networks PUMA: A programmable ultra-efficient memristor-based accelerator for machine learning inference

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.099691Z

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 29ddc0de-f928-488f-90f3-3a1c8f65798d · outbound

This paper cites A computing-in-memory macro based on three-dimensional resistive random-access memory.

Machine Intelligence on Wireless Edge Networks A computing-in-memory macro based on three-dimensional resistive random-access memory

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.089635Z

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 78102055-c7b8-43b4-8045-c453bf4f6911 · outbound

This paper cites Fast and robust analog in-memory deep neu- ral network training.

Machine Intelligence on Wireless Edge Networks Fast and robust analog in-memory deep neu- ral network training

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.079286Z

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 529b91d9-0a4c-4dca-a290-c250f123c82e · outbound

This paper cites The inherent adversarial robustness of analog in-memory computing.

Machine Intelligence on Wireless Edge Networks The inherent adversarial robustness of analog in-memory computing

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.069722Z

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 2b629d85-83d9-456b-bef0-7c2b4769485f · outbound

This paper cites In-memory computing with resistive memory circuits: Status and outlook.

Machine Intelligence on Wireless Edge Networks In-memory computing with resistive memory circuits: Status and outlook

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.059361Z

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 d97c3cb8-4cb8-4ae5-889c-10d2d0477e22 · outbound

This paper cites A crossbar array of magnetoresistive memory devices for in-memory computing.

Machine Intelligence on Wireless Edge Networks A crossbar array of magnetoresistive memory devices for in-memory computing

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.049068Z

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 ea4c213e-a6ed-4da2-8635-7aa45122983b · outbound

This paper cites A 2941-tops/w charge-domain 10t sram compute-in-memory for ternary neural network.

Machine Intelligence on Wireless Edge Networks A 2941-tops/w charge-domain 10t sram compute-in-memory for ternary neural network

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.038691Z

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 cb7c2692-af22-4c14-b447-dfac4deb8f42 · outbound

This paper cites Dou- ble mac on a cell: A 22-nm 8t-sram based analog in-memory 13 accelerator for binary/ternary neural networks featuring split wordline.

Machine Intelligence on Wireless Edge Networks Dou- ble mac on a cell: A 22-nm 8t-sram based analog in-memory 13 accelerator for binary/ternary neural networks featuring split wordline

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.029051Z

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 ff43301d-94a4-419a-b74c-42a1c134ab4d · outbound

This paper cites Power-efficient combinatorial opti- mization using intrinsic noise in memristor hopfield neural networks.

Machine Intelligence on Wireless Edge Networks Power-efficient combinatorial opti- mization using intrinsic noise in memristor hopfield neural networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.018578Z

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 65670fca-5391-4a74-bd2e-e3bb8036b44e · outbound

This paper cites A 64-core mixed-signal in- memory compute chip based on phase-change memory for deep neural network inference.

Machine Intelligence on Wireless Edge Networks A 64-core mixed-signal in- memory compute chip based on phase-change memory for deep neural network inference

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:28.008506Z

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 8d0bcc0d-bd7d-4217-9b80-39ff3fb592f6 · outbound

This paper cites Multpim: Fast stateful multiplication for processing-in- memory.

Machine Intelligence on Wireless Edge Networks Multpim: Fast stateful multiplication for processing-in- memory

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.998895Z

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 5d2814ca-58d5-4799-a5a9-8276c68e2100 · outbound

This paper cites Mat- pim: Accelerating matrix operations with memristive stateful logic.

Machine Intelligence on Wireless Edge Networks Mat- pim: Accelerating matrix operations with memristive stateful logic

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.989663Z

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 73aeb4ec-a0b9-4175-aa67-8c815d00c4d3 · outbound

This paper cites Magic—memristor-aided logic.

Machine Intelligence on Wireless Edge Networks Magic—memristor-aided logic

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.980283Z

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 18239d83-9294-40a9-a9ac-8217572b8390 · outbound

This paper cites Quantized neural networks: Train- ing neural networks with low precision weights and activa- tions.

Machine Intelligence on Wireless Edge Networks Quantized neural networks: Train- ing neural networks with low precision weights and activa- tions

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.971008Z

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 296cbfec-c92c-4867-9c7d-9af13c634bb0 · outbound

This paper cites Binarized neural networks.

Machine Intelligence on Wireless Edge Networks Binarized neural networks

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.960822Z

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 490e3062-342b-4647-8d11-45321bd1003b · outbound

This paper cites Powering ai at the edge: A robust, memristor- based binarized neural network with near-memory computing and miniaturized solar cell.

Machine Intelligence on Wireless Edge Networks Powering ai at the edge: A robust, memristor- based binarized neural network with near-memory computing and miniaturized solar cell

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.950755Z

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 dc8955e7-c9a6-4c90-8bac-a6b69633efa6 · outbound

This paper cites Computation over multiple-access channels.

Machine Intelligence on Wireless Edge Networks Computation over multiple-access channels

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.940947Z

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 25df58de-0bdf-4796-afce-571b5fbaf85b · outbound

This paper cites Robust ana- log function computation via wireless multiple-access chan- nels.

Machine Intelligence on Wireless Edge Networks Robust ana- log function computation via wireless multiple-access chan- nels

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.932099Z

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 4a6b8649-f64e-4048-be0c-cf0cd68d9fa9 · outbound

This paper cites Nomographic functions: Efficient computation in clustered gaussian sensor networks.

Machine Intelligence on Wireless Edge Networks Nomographic functions: Efficient computation in clustered gaussian sensor networks

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.921716Z

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 60779c29-1c4b-4bcc-a51a-c1034f2246d8 · outbound

This paper cites A survey on over-the-air com- putation.

Machine Intelligence on Wireless Edge Networks A survey on over-the-air com- putation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.911118Z

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 58a7e4de-1607-4052-b84d-450ea25d5bfc · outbound

This paper cites AirNN: Over-the- air computation for neural networks via reconfigurable intel- ligent surfaces.

Machine Intelligence on Wireless Edge Networks AirNN: Over-the- air computation for neural networks via reconfigurable intel- ligent surfaces

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.901195Z

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 959b11a2-71c5-4967-8daa-aa0b4faf3898 · outbound

This paper cites AirFC: Designing fully connected layers for neural networks with wireless sig- nals.

Machine Intelligence on Wireless Edge Networks AirFC: Designing fully connected layers for neural networks with wireless sig- nals

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.889690Z

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 be82e15d-a05e-4650-b84d-118ad3312b3c · outbound

This paper cites Wireless distributed matrix-vector multiplica- tion using over-the-air computation and analog coding.

Machine Intelligence on Wireless Edge Networks Wireless distributed matrix-vector multiplica- tion using over-the-air computation and analog coding

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.879231Z

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 31c3919a-bc13-442a-b5c8-d38dca280e47 · outbound

This paper cites Universal Approximation with XL MIMO Systems: OTA Classification via Trainable Analog Combining.

Machine Intelligence on Wireless Edge Networks Universal Approximation with XL MIMO Systems: OTA Classification via Trainable Analog Combining

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:27.367161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec85f7bf-ba7b-4773-bd59-f7bde312fb8e · outbound

This paper cites Computing functions over-the-air using digital mod- ulations.

Machine Intelligence on Wireless Edge Networks Computing functions over-the-air using digital mod- ulations

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.776752Z

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 8820fbe4-2ad5-47c8-a184-f771131fffcc · outbound

This paper cites A reconfigurable linear rf analog processor for realizing mi- crowave artificial neural network.

Machine Intelligence on Wireless Edge Networks A reconfigurable linear rf analog processor for realizing mi- crowave artificial neural network

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.766112Z

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 d673082d-ec16-41d3-a71b-3d018a3db7a3 · outbound

This paper cites An integrated microwave neu- ral network for broadband computation and communication.

Machine Intelligence on Wireless Edge Networks An integrated microwave neu- ral network for broadband computation and communication

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.755214Z

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 dbd121fb-ee39-48c9-92e3-cad4d3f2b94b · outbound

This paper cites Mi- crowave signal processing using an analog quantum reservoir computer.

Machine Intelligence on Wireless Edge Networks Mi- crowave signal processing using an analog quantum reservoir computer

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.745073Z

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 b0e801f1-facb-42e9-800e-4edf65cc1b56 · outbound

This paper cites A precise four-quadrant multiplier with sub- nanosecond response.

Machine Intelligence on Wireless Edge Networks A precise four-quadrant multiplier with sub- nanosecond response

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.734736Z

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 2d980232-6cab-442f-b6d3-9d02ee17ef58 · outbound

This paper cites Low voltage per- formance of a microwave CMOS Gilbert cell mixer.

Machine Intelligence on Wireless Edge Networks Low voltage per- formance of a microwave CMOS Gilbert cell mixer

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.723139Z

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 32e81438-02c0-4c10-8102-6ee80cf5fd2b · outbound

This paper cites Coaxial frequency mixer, 300–4300 MHz.

Machine Intelligence on Wireless Edge Networks Coaxial frequency mixer, 300–4300 MHz

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.712211Z

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 b6601a47-6bb3-4119-b1c6-eb6daf8cef76 · outbound

This paper cites Reconsidering os memory optimizations in the presence of disaggregated memory.

Machine Intelligence on Wireless Edge Networks Reconsidering os memory optimizations in the presence of disaggregated memory

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.702246Z

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 8c4cc3de-58d6-43e4-94ca-ddbc0d5d9d9b · outbound

This paper cites Thermal agitation of electric charge in con- ductors.

Machine Intelligence on Wireless Edge Networks Thermal agitation of electric charge in con- ductors

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.692302Z

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 bc80d65a-cbde-4d9e-afca-3066e187ea33 · outbound

This paper cites Irreversibility and generalized noise.

Machine Intelligence on Wireless Edge Networks Irreversibility and generalized noise

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.681345Z

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 de4b6638-6a0f-4a82-b1a7-0496811e0409 · outbound

This paper cites Disaggregated Deep Learning via In-Physics Computing at Radio Frequency.

Machine Intelligence on Wireless Edge Networks Disaggregated Deep Learning via In-Physics Computing at Radio Frequency

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:07:27.487817Z

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 061b4afb-20eb-4460-b626-2f9293a959fe · outbound

This paper cites A 0.75-million-point fourier-transform chip for frequency-sparse signals.

Machine Intelligence on Wireless Edge Networks A 0.75-million-point fourier-transform chip for frequency-sparse signals

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.669407Z

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 529cd0b9-eefa-40bb-b910-4011f3dff1d9 · outbound

This paper cites An IEEE 802.11a/g/p OFDM receiver for GNU Radio.

Machine Intelligence on Wireless Edge Networks An IEEE 802.11a/g/p OFDM receiver for GNU Radio

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.658138Z

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 3e0637bb-7c38-4e23-b144-d12d1389755c · outbound

This paper cites Ex- perimentally realized in situ backpropagation for deep learn- ing in photonic neural networks.

Machine Intelligence on Wireless Edge Networks Ex- perimentally realized in situ backpropagation for deep learn- ing in photonic neural networks

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.647455Z

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 138fc9bf-5fa2-4480-ba80-7274a09e46f9 · outbound

This paper cites Large-scale optical neural net- works based on photoelectric multiplication.

Machine Intelligence on Wireless Edge Networks Large-scale optical neural net- works based on photoelectric multiplication

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.634979Z

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 35944593-9b34-46cc-9269-b4703ae01d5c · outbound

This paper cites RF-Photonic Deep Learning Processor with Shannon-Limited Data Movement.

Machine Intelligence on Wireless Edge Networks RF-Photonic Deep Learning Processor with Shannon-Limited Data Movement

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:07:27.473373Z

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 7c930411-928f-4de0-92da-46a9e07a8e15 · outbound

This paper cites Layer Normalization.

Machine Intelligence on Wireless Edge Networks Layer Normalization

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:27.423313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9885473-4266-424c-a9b6-e95a5b43e305 · outbound

This paper cites Transformers without normalization.

Machine Intelligence on Wireless Edge Networks Transformers without normalization

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:07:27.624341Z

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