Paper Citation Record · LEDGER

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers

As of 15 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:1909.02384.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1909.02384 v2

Coverage vector

measured 38 of 38 reference resolution

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measured 38 of 38 standing notices

One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation 56340b36-44b1-4eee-8b1b-e6c8ae8cc5f2 · outbound

This paper cites Deep learning.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Deep learning

Reference 1

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This paper cites Image denoising and inpainting with deep neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Image denoising and inpainting with deep neural networks

Reference 2

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Observation e49c68dc-11af-4539-bba6-75340e9d6dc1 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 3

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This paper cites A uniﬁed archi- tecture for natural language processing: Deep neural networks with multitask learning.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers A uniﬁed archi- tecture for natural language processing: Deep neural networks with multitask learning

Reference 4

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Observation 39f4c37b-2509-4b8b-9000-2ac0e49d629b · outbound

This paper cites Creating more intelligent robots through brain-inspired computing.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Creating more intelligent robots through brain-inspired computing

Reference 5

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Observation 4b858031-3ea5-46d6-bffd-71a857e2dabb · outbound

This paper cites Resiliency of Deep Neural Networks under Quantization.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Resiliency of Deep Neural Networks under Quantization

Reference 6

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Observation 9817df7a-0064-4c2c-8fe4-b9275b9557ae · outbound

This paper cites Binaryconnect: Training deep neural networks with binary weights during propagations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Binaryconnect: Training deep neural networks with binary weights during propagations

Reference 7

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Observation c06fc462-d50c-4fba-b0db-d070854bfa42 · outbound

This paper cites Xnor-net: Imagenet classiﬁcation using binary convolutional neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Xnor-net: Imagenet classiﬁcation using binary convolutional neural networks

Reference 8

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Observation f8b5225e-5af1-43af-84a8-7f031f0ac840 · outbound

This paper cites Extremely low bit neural network: Squeeze the last bit out with admm.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Extremely low bit neural network: Squeeze the last bit out with admm

Reference 9

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Observation d9bfcb84-e71c-4990-b981-a95d825cc181 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 10

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Observation ed344030-fc6c-4040-8475-ea146ae62916 · outbound

This paper cites Gxnor-net: Training deep neural networks with ternary weights and activations without full-precision memory under a uniﬁed discretization framework.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Gxnor-net: Training deep neural networks with ternary weights and activations without full-precision memory under a uniﬁed discretization framework

Reference 11

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Observation a7048bfa-5013-4379-af02-c9ef3e9b793b · outbound

This paper cites Training deep neural networks with 8-bit ﬂoating point numbers.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Training deep neural networks with 8-bit ﬂoating point numbers

Reference 12

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Observation 882ed9e3-b476-4be7-93d1-641f8a098414 · outbound

This paper cites Scalable methods for 8-bit training of neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Scalable methods for 8-bit training of neural networks

Reference 13

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Observation 9a42b818-b4c4-444c-884a-02e5a45b75f7 · outbound

This paper cites Mixed Precision Training.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Mixed Precision Training

Reference 14

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Observation 1dedfcac-1d28-43ad-b376-4f933d1a8d95 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 15

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Observation db6c66e6-c6ea-4f71-a7bd-167175df4a7e · outbound

This paper cites Mixed Precision Training of Convolutional Neural Networks using Integer Operations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Mixed Precision Training of Convolutional Neural Networks using Integer Operations

Reference 16

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Observation cbd3e87b-a798-4156-884b-1b3a08bf8dd5 · outbound

This paper cites Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm

Reference 17

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Observation 0363ad4c-a7c8-4c31-b95f-270b8471b006 · outbound

This paper cites Training and Inference with Integers in Deep Neural Networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Training and Inference with Integers in Deep Neural Networks

Reference 18

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Observation 8472cee9-1909-4e7c-b19b-3e4c4b5b3139 · outbound

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

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Gradient-based learning applied to document recognition

Reference 19

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Observation f7ce22d1-251f-43dd-9c57-349934a018e2 · outbound

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

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

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This paper cites Imagenet classiﬁcation with deep convolutional neural networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Imagenet classiﬁcation with deep convolutional neural networks

Reference 21

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Observation 27005cda-b09d-45b3-ba57-f359b8f44571 · outbound

This paper cites On the momentum term in gradient descent learning algorithms.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers On the momentum term in gradient descent learning algorithms

Reference 22

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Observation 0559da31-5e0a-4c40-bd64-178a21394dd2 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Adam: A Method for Stochastic Optimization

Reference 23

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This paper cites Imagenet: A large-scale hierarchical image database.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Imagenet: A large-scale hierarchical image database

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This paper cites Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

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Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Neural networks for machine learning

Reference 26

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Observation 2fba2dc1-a00f-4b7f-865b-81c120087dcb · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

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This paper cites Quantized neural net- works: Training neural networks with low precision weights and activations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Quantized neural net- works: Training neural networks with low precision weights and activations

Reference 28

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Observation c68ea7c8-1550-4c8f-a141-0430df83a85a · outbound

This paper cites Balanced quantization: An effec- tive and efﬁcient approach to quantized neural net- works.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Balanced quantization: An effec- tive and efﬁcient approach to quantized neural net- works

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Observation 97578bb7-ad9e-4672-8d10-7906ba0a6a3d · outbound

This paper cites Effective Quantization Methods for Recurrent Neural Networks.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Effective Quantization Methods for Recurrent Neural Networks

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This paper cites Delving deep into rectiﬁers: Surpassing human-level performance on imagenet classiﬁcation.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Delving deep into rectiﬁers: Surpassing human-level performance on imagenet classiﬁcation

Reference 31

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Observation 2959e482-c4db-4459-8fa4-6ad32a10b9c9 · outbound

This paper cites Tbn: Convolutional neural network with ternary inputs and binary weights.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Tbn: Convolutional neural network with ternary inputs and binary weights

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Observation 8a416904-c95e-46ec-8bcd-7b13a759682b · outbound

This paper cites Learning Sparse Low-Precision Neural Networks With Learnable Regularization.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Learning Sparse Low-Precision Neural Networks With Learnable Regularization

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This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

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This paper cites Using learning rate schedules for deep learning models in python with keras, 2016.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Using learning rate schedules for deep learning models in python with keras, 2016

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Observation a7d6e19a-7ffd-42c7-91dc-ff94b17d43b6 · outbound

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Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Learning rate schedules and adaptive learning rate methods for deep learning

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Observation 1a0478b5-6b47-404e-9633-0499f7b3fc5a · outbound

This paper cites Finite-time bound- edness of large-scale systems with actuator faults and gain ﬂuctuations.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Finite-time bound- edness of large-scale systems with actuator faults and gain ﬂuctuations

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This paper cites Single precision in weather forecasting models: An evaluation with the ifs.

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Single precision in weather forecasting models: An evaluation with the ifs

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