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Neural Turing machine

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1537: 1517: 237:. The first stable open-source implementation was published in 2018 at the 27th International Conference on Artificial Neural Networks, receiving a best-paper award. Other open source implementations of NTMs exist but as of 2018 they are not sufficiently stable for production use. The developers either report that the 1411: 402: 403:"Best-Paper Award for our Publication "Implementing Neural Turing Machines" at the 27th International Conference on Artificial Neural Networks | Prof. Joeran Beel (TCD Dublin)" 1253: 659: 222:
resources, which it interacts with through attentional mechanisms. The memory interactions are differentiable end-to-end, making it possible to optimize them using
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during training for unknown reasons and cause training to fail; report slow convergence; or do not report the speed of learning of their implementation.
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Graves, Alex; Wayne, Greg; Danihelka, Ivo (2014). "Neural Turing Machines".
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Collier, Mark; Beel, Joeran (2018), "Implementing Neural Turing Machines",
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Trinity College Dublin, School of Computer Science and Statistics Blog
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that control where the memory is active, and improve performance.
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Artificial Neural Networks and Machine Learning – ICANN 2018
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The authors of the original NTM paper did not publish their
618:"DeepMind's Differentiable Neural Network Thinks Deeply" 323:, Springer International Publishing, pp. 94–104, 1425: 1369: 1298: 1231: 1103: 1003: 996: 950: 914: 857: 733: 673: 218:An NTM has a neural network controller coupled to 251:are an outgrowth of Neural Turing machines, with 653: 160: 8: 1000: 660: 646: 638: 167: 153: 15: 328: 282: 241:of their implementation sometimes become 272: 270: 268: 264: 199:et al. in 2014. NTMs combine the fuzzy 127: 51: 25: 18: 587: 585: 560: 558: 533: 531: 7: 1498:Generative adversarial network (GAN) 506: 504: 478: 476: 451: 449: 424: 422: 378:"MarkPKCollier/NeuralTuringMachine" 14: 484:"yeoedward/Neural-Turing-Machine" 1536: 1535: 1515: 512:"camigord/Neural-Turing-Machine" 457:"chiggum/Neural-Turing-Machines" 195:. The approach was published by 249:Differentiable neural computers 70:Nondeterministic Turing machine 1448:Recurrent neural network (RNN) 1438:Differentiable neural computer 1: 1493:Variational autoencoder (VAE) 1453:Long short-term memory (LSTM) 720:Computational learning theory 1572:Neural network architectures 1473:Convolutional neural network 593:"loudinthecloud/pytorch-ntm" 347:10.1007/978-3-030-01424-7_10 85:Probabilistic Turing machine 1468:Multilayer perceptron (MLP) 401:Beel, Joeran (2018-10-20). 1588: 1544:Artificial neural networks 1458:Gated recurrent unit (GRU) 684:Differentiable programming 539:"carpedm20/NTM-tensorflow" 110:Unambiguous Turing machine 95:Multi-track Turing machine 60:Alternating Turing machine 34:Turing machine equivalents 1511: 877:Artificial neural network 700:Automatic differentiation 705:Neuromorphic engineering 668:Differentiable computing 189:recurrent neural network 115:Universal Turing machine 100:Symmetric Turing machine 90:Multitape Turing machine 1478:Residual neural network 894:Artificial Intelligence 141:Category:Turing machine 39:Turing machine examples 228:long short-term memory 213:programmable computers 75:Quantum Turing machine 44:Turing machine gallery 1433:Neural Turing machine 1021:Human image synthesis 622:www.i-programmer.info 566:"snipsco/ntm-lasagne" 181:neural Turing machine 65:Neural Turing machine 1524:Computer programming 1503:Graph neural network 1078:Text-to-video models 1056:Text-to-image models 904:Large language model 889:Scientific computing 695:Statistical manifold 690:Information geometry 253:attention mechanisms 105:Total Turing machine 870:In-context learning 710:Pattern recognition 339:2018arXiv180708518C 80:Post–Turing machine 1463:Echo state network 1351:JĂĽrgen Schmidhuber 1046:Facial recognition 1041:Speech recognition 951:Software libraries 1559: 1558: 1321:Stephen Grossberg 1294: 1293: 177: 176: 1579: 1549:Machine learning 1539: 1538: 1519: 1274:Action selection 1264:Self-driving car 1071:Stable Diffusion 1036:Speech synthesis 1001: 865:Machine learning 741:Gradient descent 662: 655: 648: 639: 632: 631: 629: 628: 613: 607: 606: 604: 603: 589: 580: 579: 577: 576: 562: 553: 552: 550: 549: 535: 526: 525: 523: 522: 508: 499: 498: 496: 495: 480: 471: 470: 468: 467: 453: 444: 443: 441: 440: 426: 417: 416: 414: 413: 398: 392: 391: 389: 388: 374: 368: 367: 332: 316: 310: 309: 307: 305: 295: 289: 288: 286: 274: 226:. An NTM with a 224:gradient descent 203:capabilities of 201:pattern matching 169: 162: 155: 16: 1587: 1586: 1582: 1581: 1580: 1578: 1577: 1576: 1562: 1561: 1560: 1555: 1507: 1421: 1387:Google DeepMind 1365: 1331:Geoffrey Hinton 1290: 1227: 1153:Project Debater 1099: 997:Implementations 992: 946: 910: 853: 795:Backpropagation 729: 715:Tensor calculus 669: 666: 636: 635: 626: 624: 616:Administrator. 615: 614: 610: 601: 599: 591: 590: 583: 574: 572: 564: 563: 556: 547: 545: 537: 536: 529: 520: 518: 510: 509: 502: 493: 491: 482: 481: 474: 465: 463: 455: 454: 447: 438: 436: 430:"snowkylin/ntm" 428: 427: 420: 411: 409: 400: 399: 395: 386: 384: 376: 375: 371: 357: 318: 317: 313: 303: 301: 297: 296: 292: 276: 275: 266: 261: 220:external memory 205:neural networks 173: 20:Turing machines 12: 11: 5: 1585: 1583: 1575: 1574: 1564: 1563: 1557: 1556: 1554: 1553: 1552: 1551: 1546: 1533: 1532: 1531: 1526: 1512: 1509: 1508: 1506: 1505: 1500: 1495: 1490: 1485: 1480: 1475: 1470: 1465: 1460: 1455: 1450: 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Retrieved 293: 247: 232: 217: 184: 180: 178: 120:Zeno machine 64: 1540:Categories 1488:Autoencoder 1443:Transformer 1311:Alex Graves 1259:OpenAI Five 1163:IBM Watsonx 785:Convolution 763:Overfitting 235:source code 209:algorithmic 197:Alex Graves 191:model of a 136:Alan Turing 1529:Technology 1382:EleutherAI 1341:Fei-Fei Li 1336:Yann LeCun 1249:Q-learning 1232:Decisional 1158:IBM Watson 1066:Midjourney 958:TensorFlow 805:Activation 758:Regression 753:Clustering 627:2016-10-20 602:2018-10-20 575:2018-10-20 548:2018-10-20 521:2018-10-20 494:2018-10-20 466:2018-10-20 439:2018-10-20 412:2018-10-20 387:2018-10-20 330:1807.08518 259:References 1412:MIT CSAIL 1377:Anthropic 1346:Andrew Ng 1244:AlphaZero 1088:VideoPoet 1051:AlphaFold 988:MindSpore 942:SpiNNaker 937:Memristor 844:Diffusion 820:Rectifier 800:Batchnorm 780:Attention 775:Adversary 284:1410.5401 239:gradients 211:power of 207:with the 1566:Category 1520:Portals 1279:Auto-GPT 1111:Word2vec 915:Hardware 832:Datasets 734:Concepts 365:49908746 52:Variants 1402:Meta AI 1239:AlphaGo 1223:PanGu-ÎŁ 1193:ChatGPT 1168:Granite 1116:Seq2seq 1095:Whisper 1016:WaveNet 1011:AlexNet 983:Flux.jl 963:PyTorch 815:Sigmoid 810:Softmax 675:General 335:Bibcode 304:May 17, 187:) is a 128:Science 26:Machine 1417:Huawei 1397:OpenAI 1299:People 1269:MuZero 1131:Gemini 1126:Claude 1061:DALL-E 973:Theano 597:GitHub 570:GitHub 543:GitHub 516:GitHub 488:GitHub 461:GitHub 434:GitHub 382:GitHub 363:  353:  1483:Mamba 1254:SARSA 1218:LLaMA 1213:BLOOM 1198:GPT-J 1188:GPT-4 1183:GPT-3 1178:GPT-2 1173:GPT-1 1136:LaMDA 968:Keras 361:S2CID 325:arXiv 279:arXiv 1407:Mila 1208:PaLM 1141:Bard 1121:BERT 1104:Text 1083:Sora 351:ISBN 306:2016 1148:NMT 1031:OCR 1026:HWR 978:JAX 932:VPU 927:TPU 922:IPU 746:SGD 343:doi 243:NaN 215:. 185:NTM 1568:: 620:. 595:. 584:^ 568:. 557:^ 541:. 530:^ 514:. 503:^ 486:. 475:^ 459:. 448:^ 432:. 421:^ 405:. 380:. 359:, 349:, 341:, 333:, 267:^ 179:A 661:e 654:t 647:v 630:. 605:. 578:. 551:. 524:. 497:. 469:. 442:. 415:. 390:. 345:: 337:: 327:: 308:. 287:. 281:: 183:( 168:e 161:t 154:v

Index

Turing machines
Turing machine equivalents
Turing machine examples
Turing machine gallery
Alternating Turing machine
Neural Turing machine
Nondeterministic Turing machine
Quantum Turing machine
Post–Turing machine
Probabilistic Turing machine
Multitape Turing machine
Multi-track Turing machine
Symmetric Turing machine
Total Turing machine
Unambiguous Turing machine
Universal Turing machine
Zeno machine
Alan Turing
Category:Turing machine
v
t
e
recurrent neural network
Turing machine
Alex Graves
pattern matching
neural networks
algorithmic
programmable computers
external memory

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