SpikeFI: A Fault Injection Framework for Spiking Neural Networks | Paper Citation Record

Observation a82fdaae-108a-43fe-8ddb-44ca26824044 · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Towards spike-based machine intelligence with neuromorphic computing,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:29.049367Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4d74ebf6-ed9c-4ef5-b366-c507520e6276 · outbound

This paper cites Opportunities for neuromorphic computing algorithms and applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Opportunities for neuromorphic computing algorithms and applications,

Reference 2

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 746eaf0e-7e02-4eb7-94d1-f09903b0a5a9 · outbound

This paper cites The SpiNNaker Project,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks The SpiNNaker Project,

Reference 3

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Observation aa45a333-24b9-4d3b-86a1-61c152957c8d · outbound

This paper cites A million spiking-neuron integrated circuit with a scalable communication network and interface,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A million spiking-neuron integrated circuit with a scalable communication network and interface,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:29.006919Z

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Observation 76a24d39-0ce8-43da-8c14-76b212909d1f · outbound

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

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.991413Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5040ed34-a43f-4c54-9e90-949e978c5ae7 · outbound

This paper cites A wafer-scale neuromorphic hardware system for large-scale neural modeling,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A wafer-scale neuromorphic hardware system for large-scale neural modeling,

Reference 6

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e1ba9a8-d719-4529-ba2c-a59d047db139 · outbound

This paper cites Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.948234Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7402b30c-e5b7-41f8-a31f-92e1c5b5fc70 · outbound

This paper cites Machine learning-based test pattern generation for neuromorphic chips,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Machine learning-based test pattern generation for neuromorphic chips,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aab91c56-74e3-4998-be77-8a6d077f08a6 · outbound

This paper cites Automatic test configuration and pattern generation (atcpg) for neuromorphic chips,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Automatic test configuration and pattern generation (atcpg) for neuromorphic chips,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.900801Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6e3befd9-a50d-4568-b5ef-4b052a5e7249 · outbound

This paper cites Compact functional testing for neuromorphic computing circuits,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Compact functional testing for neuromorphic computing circuits,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.875996Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f5b6c5c1-b24c-429b-b2a8-a5d9b8aa41f3 · outbound

This paper cites On-line testing of neuromorphic hardware,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks On-line testing of neuromorphic hardware,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.858958Z

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Observation 73c0ed19-6533-4627-8ce3-295c6d8a00cc · outbound

This paper cites Resilience and robustness of spiking neural networks for neuromorphic systems,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Resilience and robustness of spiking neural networks for neuromorphic systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.843243Z

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Observation a7cd905a-0fa0-43c8-81ff-b5b7be4bb361 · outbound

This paper cites Automatic abstraction and fault tolerance in cortical microachitectures,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Automatic abstraction and fault tolerance in cortical microachitectures,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.827758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f6921932-4945-4279-8297-60a836b3c8f3 · outbound

This paper cites Assessing self-repair on FPGAs with biologically realistic astrocyte-neuron networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Assessing self-repair on FPGAs with biologically realistic astrocyte-neuron networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.813762Z

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Observation 6bf73ac4-b387-4cbc-bb01-9f651f5ed013 · outbound

This paper cites Homeostatic fault tolerance in spiking neural networks: A dynamic hardware perspective,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Homeostatic fault tolerance in spiking neural networks: A dynamic hardware perspective,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.795888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9671e3c7-7ba2-47d1-a7dd-f88d12af3007 · outbound

This paper cites SPAN- NER: A self-repairing spiking neural network hardware architecture,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SPAN- NER: A self-repairing spiking neural network hardware architecture,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.779235Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db25c855-ebfd-4493-8d41-7a1eeb89dfb2 · outbound

This paper cites Self-testing analog spiking neuron circuit,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Self-testing analog spiking neuron circuit,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.758502Z

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Observation 4e978827-74e2-49b0-ab69-2d1cbeecc66b · outbound

This paper cites Neuron fault tolerance in spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Neuron fault tolerance in spiking neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.738432Z

Source-reported events for the cited work

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Observation 784aa545-3f2c-436a-9e79-d570c0f45a94 · outbound

This paper cites SoftSNN: Low-cost fault tolerance for spiking neural network accelerators under soft errors,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SoftSNN: Low-cost fault tolerance for spiking neural network accelerators under soft errors,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.716601Z

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Observation 40728d35-c3e2-47e3-9f90-24dc4d85e995 · outbound

This paper cites A resilience framework for synapse weight errors and firing threshold perturbations in RRAM spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A resilience framework for synapse weight errors and firing threshold perturbations in RRAM spiking neural networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.701726Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 604b84a9-b77b-4243-a653-072d67c9bbb2 · outbound

This paper cites Reliability analysis of a spiking neural network hardware accelerator,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Reliability analysis of a spiking neural network hardware accelerator,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.685205Z

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Observation a040173c-d262-419c-9d27-0a271df03848 · outbound

This paper cites Special session: Reliability of hardware-implemented spiking neural networks (SNN),.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Special session: Reliability of hardware-implemented spiking neural networks (SNN),

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.670216Z

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Observation 0c7082de-5fd7-4767-a952-af3a56d6985d · outbound

This paper cites SpikingJET: Enhancing fault injection for fully and convolutional spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SpikingJET: Enhancing fault injection for fully and convolutional spiking neural networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.651899Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a00860c-3b72-42a4-8db6-18e08d9c35a5 · outbound

This paper cites Training spiking neural networks using lessons from deep learning,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Training spiking neural networks using lessons from deep learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.636954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a578f3e-afa7-4f2e-80f1-25f91b4e6282 · outbound

This paper cites SLAYER: Spike layer error reassign- ment in time,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SLAYER: Spike layer error reassign- ment in time,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.621024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ee163186-87ec-49b3-9dfb-3a9f521a99bd · outbound

This paper cites Understanding error propagation in deep learning neural network (DNN) accelerators and applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Understanding error propagation in deep learning neural network (DNN) accelerators and applications,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.607376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 86bec341-2e83-4f24-a657-13e06014ccce · outbound

This paper cites Ares: A framework for quantifying the resilience of deep neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Ares: A framework for quantifying the resilience of deep neural networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.592360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0258d5b7-2614-414c-93cd-0ed9afd72c19 · outbound

This paper cites PyTorchFI: A runtime perturbation tool for DNNs,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks PyTorchFI: A runtime perturbation tool for DNNs,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.579339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 746ae228-1cdf-4358-82b9-6ada1cf1802b · outbound

This paper cites TensorFI: A flexible fault injection framework for tensor- flow applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks TensorFI: A flexible fault injection framework for tensor- flow applications,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.566568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b5e287c-a568-4da4-be5d-91804f49e6aa · outbound

This paper cites Fault injection for TensorFlow applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Fault injection for TensorFlow applications,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.553379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6a95bf9-c676-43c3-abe9-0ab99ffeec6c · outbound

This paper cites FIdelity: Efficient resilience analysis framework for deep learning accelerators,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks FIdelity: Efficient resilience analysis framework for deep learning accelerators,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.540720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41888f1a-5db6-4287-a534-de9615d8739a · outbound

This paper cites Fast and accurate error simulation for CNNs against soft errors,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Fast and accurate error simulation for CNNs against soft errors,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.522093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5012b43a-08a4-4e51-89aa-a80c3f627c20 · outbound

This paper cites Emulating the effects of radiation-induced soft-errors for the reliability assessment of neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Emulating the effects of radiation-induced soft-errors for the reliability assessment of neural networks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.507889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 031d3457-bbea-4af2-9673-0f22f159dead · outbound

This paper cites BinFI: An efficient fault injector for safety-critical machine learning systems,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks BinFI: An efficient fault injector for safety-critical machine learning systems,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.489317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7deab69a-70d4-4b27-8bfa-44c4ded0ef2e · outbound

This paper cites Functional criticality analysis of structural faults in AI accelerators,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Functional criticality analysis of structural faults in AI accelerators,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.462454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 06219cac-eed9-4e6e-9001-313f0583af60 · outbound

This paper cites SCI-FI: a smart, accurate and unintrusive fault-injector for deep neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SCI-FI: a smart, accurate and unintrusive fault-injector for deep neural networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.439848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 005ce207-0359-41ca-af6a-2999c613be2c · outbound

This paper cites Assessing convolutional neural networks reliability through statistical fault injections,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Assessing convolutional neural networks reliability through statistical fault injections,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.421118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dff318f5-de31-4e2a-8309-25ba7826a8dc · outbound

This paper cites SASSIFI: An architecture-level fault injection tool for GPU application resilience evaluation,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SASSIFI: An architecture-level fault injection tool for GPU application resilience evaluation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.404191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b5319b82-4938-4bfa-a872-ee9a1ec9abd7 · outbound

This paper cites NVBitFI: Dynamic fault injection for GPUs,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks NVBitFI: Dynamic fault injection for GPUs,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.390053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5003e22-3f21-4304-86a9-b9cdf52363ca · outbound

This paper cites Testability and dependability of AI hardware: Survey, trends, challenges, and perspectives,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Testability and dependability of AI hardware: Survey, trends, challenges, and perspectives,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.367326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cdd145b9-6d8d-4198-ba1f-5cf1a644cf65 · outbound

This paper cites A survey on deep learning resilience assessment methodologies,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A survey on deep learning resilience assessment methodologies,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.344050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9a4d4b67-3592-49d3-92f3-1c25099f61ec · outbound

This paper cites Testing and reliability of spiking neural networks: A review of the state-of-the-art,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Testing and reliability of spiking neural networks: A review of the state-of-the-art,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.314396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 647a80fc-e5c5-4184-8ca7-b499b8602985 · outbound

This paper cites A systematic literature review on hardware reliability assessment methods for deep neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A systematic literature review on hardware reliability assessment methods for deep neural networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.295134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f883664a-5bc8-4d71-8187-a6bdb8375826 · outbound

This paper cites Artificial neural networks for space and safety-critical applications: Reliability issues and potential solutions,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Artificial neural networks for space and safety-critical applications: Reliability issues and potential solutions,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.273717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9cff2907-6f8d-45e3-a8ce-78345e7714bd · outbound

This paper cites Networks of spiking neurons: The third generation of neural network models,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Networks of spiking neurons: The third generation of neural network models,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.243913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f03c0914-8763-4995-9f90-cd5f9a2b6c86 · outbound

This paper cites Gerstner, W.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Gerstner, W

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.227743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 607d67b6-7765-4291-a922-890b9e5faaeb · outbound

This paper cites Deep learning in spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Deep learning in spiking neural networks,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.199668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e31baef6-7424-4190-aaae-81da375bf9d6 · outbound

This paper cites Spiking neuron hardware-level fault modeling,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Spiking neuron hardware-level fault modeling,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.156168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a915a472-9e33-40c6-8374-14942611972e · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks PyTorch: An imperative style, high-performance deep learning library,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.130481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 67983f75-8743-4c68-8134-b5bfc0cf47b8 · outbound

This paper cites Converting static image datasets to spiking neuromorphic datasets using saccades,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Converting static image datasets to spiking neuromorphic datasets using saccades,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.096137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bda1c393-856a-4959-9575-6e4cbb7a279d · outbound

This paper cites A low power, fully event-based gesture recognition system,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A low power, fully event-based gesture recognition system,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.071351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a28efcc-16ad-4a42-8afd-dc9488df162d · outbound

This paper cites Gradient-based learning applied to document recognition,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Gradient-based learning applied to document recognition,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:49:28.029789Z

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