Papers › Neural Turing Machines

Neural Turing Machines

20 Oct 2014arXiv:1410.5401archive 2025-07-28

Alex Graves, Greg Wayne, Ivo Danihelka

We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.

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Code

Syntology Ran 4 of 8 code samples harvested from 5 repositories linked to this paper; 4 have no recorded run. Of those that ran: 1 ran · honoured contract; 2 ran · violated contract; 1 ran · our draft was wrong.

By repository: community (archive-listed): 6 samples from 5 repositories, 2 ran; 2 identical to code first harvested elsewhere. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

34 repositories listed; official and paper-mentioned ones first.

Darkwaqar/NTM mentioned on GitHubtf report
MarkPKCollier/NeuralTuringMachine mentioned on GitHubtfLGPL-3.0 report
SaremS/MANN mentioned on GitHub report
SourangshuGhosh/NeuralTuringMachine mentioned on GitHubtfMIT report
adityagilra/archibrain mentioned on GitHubpytorch report
ajithcodesit/Neural_Turing_Machine mentioned on GitHubtfMIT report
ajithcodesit/lstm_copy_task mentioned on GitHubtf report
camigord/Neural-Turing-Machine mentioned on GitHubtf report
carpedm20/NTM-tensorflow mentioned on GitHubtf report
clemkoa/ntm mentioned on GitHubpytorch report
dgedon/lightning-ntm mentioned on GitHubpytorch report
flomlo/ntm_keras mentioned on GitHubtf report
fuchason/NTM-keras mentioned on GitHubtfBSD-3-Clause report
jiankaiwang/dnc-py3 mentioned on GitHubtf report
jingweiz/pytorch-dnc mentioned on GitHubpytorch report
kaishengtai/torch-ntm mentioned on GitHubtorch report
loudinthecloud/pytorch-ntm mentioned on GitHubpytorchBSD-3-Clause report
mdabagia/NeuralTuringMachine mentioned on GitHubpytorch report
philippe554/MANN mentioned on GitHubtf report
qihongl/dlstm-demo mentioned on GitHubpytorch report
rs9000/Neural-Turing-machine mentioned on GitHubpytorch report
sh951011/Attention-Implementation mentioned on GitHubpytorchMIT report
shanyaanand/ntm mentioned on GitHub report
snipsco/ntm-lasagne mentioned on GitHubMIT report
snowkylin/ntm mentioned on GitHubtfLGPL-3.0 report
sooftware/Attention-Implementation mentioned on GitHubpytorch report
sooftware/nlp-attentions mentioned on GitHubpytorchMIT report
theforager/rnn_exploration mentioned on GitHubpytorch report
thehardwayguy/lstm_copy_task mentioned on GitHubtf report
theneuralbeing/ntm mentioned on GitHubpytorch report
thomlake/pytorch-attention mentioned on GitHubpytorchBSD-2-Clause report
vlgiitr/ntm-pytorch mentioned on GitHubpytorchMIT report
yeoedward/Neural-Turing-Machine mentioned on GitHubtf report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

8 samples harvested; 4 ran; 1 honoured the contract we drafted; 4 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · honoured contract
2ran · violated contract
1ran · our draft was wrong
4unverified

Licence: 2 of the 8 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from 5 repositories linked to this paper, official or community; each sample names its own and says which. Some samples are identical code Syntology first harvested from another repository; for those, this paper's copy is not located and its licence is not recorded. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

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controller_input_output_shape flomlo/ntm_keras/ntm.py community (archive-listed) ran · violated contract fingerprinted BSD-3-Clause (permissive) · 7c1a6f99d8ba140b · report
get_training_sequence clemkoa/ntm/copy_task.py community (archive-listed) ran · our draft was wrong fingerprinted MIT (permissive) · 02116da266e40b85 · report
dataloader loudinthecloud/pytorch-ntm/tasks/repeatcopytask.py community (archive-listed) unverified BSD-3-Clause (permissive) · b5063f141af96e2f · report
gen_model fuchason/NTM-keras/model_dense.py community (archive-listed) unverified BSD-3-Clause (permissive) · edea565d763b6ec5 · report
gen_model fuchason/NTM-keras/model_lstm.py community (archive-listed) unverified BSD-3-Clause (permissive) · e6e9cabffb24abab · report
generate_copy_sequence carpedm20/NTM-tensorflow/tasks/copy.py community (archive-listed) unverified MIT (permissive) · 57c4136bed9526a4 · report
BRL identical code first harvested elsewhere ran · honoured contract fingerprinted licence of this copy not recorded · 76c7df2adaf2c605 · report
str2bool identical code first harvested elsewhere ran · violated contract licence of this copy not recorded · 25c7475539e39da4 · report

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Methods

Introduced by this paper: Content-based Attention, Neural Turing Machine

Content-based AttentionLSTMNeural Turing MachineSigmoid ActivationTanh Activation

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