-
1
-
-
85026743850
-
-
CIFAR10 model for Keras
-
CIFAR10 model for Keras. https://github.com/fchollet/keras/blob/master/examples/cifar10 cnn.py
-
-
-
-
3
-
-
85026773741
-
-
Keras
-
Keras. https://keras.io
-
-
-
-
5
-
-
85026780037
-
-
Mnist, CNN network
-
Mnist, CNN network. https://github.com/fchollet/keras/blob/master/examples/mnist cnn.py
-
-
-
-
6
-
-
85026764446
-
-
Theano
-
Theano. http://deeplearning.net/software/theano/
-
-
-
-
7
-
-
85026759579
-
-
VGG16 model for Keras
-
VGG16 model for Keras. https://gist.github.com/baraldilorenzo/07d7802847aaa d0a35d3
-
-
-
-
8
-
-
85026750469
-
-
Z3
-
Z3. http://rise4fun.com/z3
-
-
-
-
9
-
-
0003722380
-
Functions of Bounded Variation and Free Discontinuity Problems. Oxford Mathematical Monographs
-
Oxford University Press, Oxford
-
Ambrosio, L., Fusco, N., Pallara, D.: Functions of Bounded Variation and Free Discontinuity Problems. Oxford Mathematical Monographs. Oxford University Press, Oxford (2000)
-
(2000)
-
-
Ambrosio, L.1
Fusco, N.2
Pallara, D.3
-
10
-
-
85040742772
-
Concrete problems in AI safety
-
Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., Mané, D.: Concrete problems in AI safety. CoRR, abs/1606.06565 (2016)
-
(2016)
Corr, Abs/1606
, pp. 06565
-
-
Amodei, D.1
Olah, C.2
Steinhardt, J.3
Christiano, P.4
Schulman, J.5
Mané, D.6
-
11
-
-
84939500710
-
Unsupervised learning of invariant representations
-
Anselmi, F., Leibo, J.Z., Rosasco, L., Mutch, J., Tacchetti, A., Poggio, T.: Unsupervised learning of invariant representations. Theoret. Comput. Sci. 633, 112–121 (2016)
-
(2016)
Theoret. Comput. Sci.
, vol.10426 LNCS
, pp. 112-121
-
-
Anselmi, F.1
Leibo, J.Z.2
Rosasco, L.3
Mutch, J.4
Tacchetti, A.5
Poggio, T.6
-
12
-
-
85026728048
-
-
CoRR, abs/1605.07262, To appear in NIPS
-
Bastani, O., Ioannou, Y., Lampropoulos, L., Vytiniotis, D., Nori, A., Criminisi, A.: Measuring neural net robustness with constraints. CoRR, abs/1605.07262 (2016). (To appear in NIPS)
-
-
-
Bastani, O.1
Ioannou, Y.2
Lampropoulos, L.3
Vytiniotis, D.4
Nori, A.5
Criminisi, A.6
-
13
-
-
84886493283
-
Evasion attacks against machine learning at test time
-
Blockeel, H., Kersting, K., Nijssen, S., Železný, F. (eds.), Springer, Heidelberg
-
Biggio, B., Corona, I., Maiorca, D., Nelson, B., Šrndić, N., Laskov, P., Giacinto, G., Roli, F.: Evasion attacks against machine learning at test time. In: Blockeel, H., Kersting, K., Nijssen, S., Železný, F. (eds.) ECML PKDD 2013. LNCS, vol. 8190, pp. 387–402. Springer, Heidelberg (2013). doi:10.1007/978-3-642-40994-3_25
-
(2013)
ECML PKDD 2013. LNCS
, vol.8190
, pp. 387-402
-
-
Biggio, B.1
Corona, I.2
Maiorca, D.3
Nelson, B.4
Šrndić, N.5
Laskov, P.6
Giacinto, G.7
Roli, F.8
-
14
-
-
0003487601
-
Neural Networks for Pattern Recognition
-
Oxford University Press, Oxford
-
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995)
-
(1995)
-
-
Bishop, C.M.1
-
15
-
-
85028075645
-
End to end learning for self-driving cars
-
Bojarski, M., Del Testa, D., Dworakowski, D., Firner, B., Flepp, B., Goyal, P., Jackel, L.D., Monfort, M., Muller, U., Zhang, J., Zhang, X., Zhao, J., Zieba, K.: End to end learning for self-driving cars. arXiv:1604.07316 (2016)
-
(2016)
Arxiv
, vol.1604
, pp. 07316
-
-
Bojarski, M.1
Del Testa, D.2
Dworakowski, D.3
Firner, B.4
Flepp, B.5
Goyal, P.6
Jackel, L.D.7
Monfort, M.8
Muller, U.9
Zhang, J.10
Zhang, X.11
Zhao, J.12
Zieba, K.13
-
16
-
-
36848999261
-
On the local behavior of spaces of natural images
-
Carlsson, G.E., Ishkhanov, T., de Silva, V., Zomorodian, A.: On the local behavior of spaces of natural images. Int. J. Comput. Vis. 76(1), 1–12 (2008)
-
(2008)
Int. J. Comput. Vis.
, vol.76
, Issue.1
, pp. 1-12
-
-
Carlsson, G.E.1
Ishkhanov, T.2
De Silva, V.3
Zomorodian, A.4
-
17
-
-
85026779959
-
-
Hendricks, L.A., Park, D.H., Akata, Z., Schiele, B., Darrell, T., Rohrbach, M.: Attentive explanations: justifying decisions and pointing to the evidence. arXiv.org/abs/1612.04757 (2016)
-
(2016)
Attentive Explanations: Justifying Decisions and Pointing to the Evidence. Arxiv.Org/Abs/1612
, pp. 04757
-
-
Hendricks, L.A.1
Park, D.H.2
Akata, Z.3
Schiele, B.4
Darrell, T.5
Rohrbach, M.6
-
18
-
-
84963525982
-
Analysis of classifiers’ robustness to adversarial perturbations
-
Fawzi, A., Fawzi, O., Frossard, P.: Analysis of classifiers’ robustness to adversarial perturbations. CoRR, abs/1502.02590 (2015)
-
(2015)
Corr, Abs/1502
, pp. 02590
-
-
Fawzi, A.1
Fawzi, O.2
Frossard, P.3
-
19
-
-
84979586198
-
Explaining and harnessing adversarial examples
-
Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. CoRR, abs/1412.6572 (2014)
-
(2014)
Corr, Abs/1412
, pp. 6572
-
-
Goodfellow, I.J.1
Shlens, J.2
Szegedy, C.3
-
20
-
-
85018687899
-
Safety verification of deep neural networks
-
Huang, X., Kwiatkowska, M., Wang, S., Wu, M.: Safety verification of deep neural networks (2016). https://arxiv.org/abs/1610.06940
-
(2016)
-
-
Huang, X.1
Kwiatkowska, M.2
Wang, S.3
Wu, M.4
-
21
-
-
85026725533
-
Reluplex: An efficient SMT solver for verifying deep neural networks
-
CAV, (2017, to appear)
-
Katz, G., Barrett, C., Dill, D., Julian, K., Kochenderfer, M.: Reluplex: an efficient SMT solver for verifying deep neural networks. In: CAV 2017 (2017, to appear)
-
(2017)
-
-
Katz, G.1
Barrett, C.2
Dill, D.3
Julian, K.4
Kochenderfer, M.5
-
22
-
-
85027699421
-
-
Kurakin, A., Goodfellow, I., Bengio, S.: Adversarial examples in the physical world. arXiv:1607.02533 (2016)
-
(2016)
Adversarial Examples in the Physical World. Arxiv
, vol.1607
, pp. 02533
-
-
Kurakin, A.1
Goodfellow, I.2
Bengio, S.3
-
23
-
-
84930630277
-
Deep learning
-
LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521, 436–444 (2015)
-
(2015)
Nature
, vol.521
, pp. 436-444
-
-
Lecun, Y.1
Bengio, Y.2
Hinton, G.3
-
24
-
-
84960344531
-
Understanding deep convolutional networks. Philos. Trans. R. Soc. Lond. A: Math. Phys. Eng. Sci. 374(2065) (2016)
-
Mallat, S.: Understanding deep convolutional networks. Philos. Trans. R. Soc. Lond. A: Math. Phys. Eng. Sci. 374(2065) (2016). ISSN 1364-503X. doi:10.1098/rsta.2015.0203
-
ISSN 1364-503X. Doi:10.1098/Rsta
, vol.2015
, pp. 0203
-
-
Mallat, S.1
-
25
-
-
85024491816
-
Deepfool: A simple and accurate method to fool deep neural networks
-
Moosavi-Dezfooli, S.-M., Fawzi, A., Frossard, P.: Deepfool: a simple and accurate method to fool deep neural networks. CoRR, abs/1511.04599 (2015)
-
(2015)
Corr, Abs/1511
, pp. 04599
-
-
Moosavi-Dezfooli, S.-M.1
Fawzi, A.2
Frossard, P.3
-
27
-
-
85026745229
-
Cleverhans v1.0.0: An adversarial machine learning library
-
Papernot, N., Goodfellow, I., Sheatsley, R., Feinman, R., McDaniel, P.: Cleverhans v1.0.0: an adversarial machine learning library. arXiv preprint arXiv:1610.00768 (2016)
-
(2016)
Arxiv Preprint Arxiv
, vol.1610
-
-
Papernot, N.1
Goodfellow, I.2
Sheatsley, R.3
Feinman, R.4
McDaniel, P.5
-
28
-
-
84978047763
-
The limitations of deep learning in adversarial settings
-
Papernot, N., McDaniel, P., Jha, S., Fredrikson, M., Celik, Z.B., Swami, A.: The limitations of deep learning in adversarial settings. In: Proceedings of the 1st IEEE European Symposium on Security and Privacy (2015)
-
(2015)
Proceedings of the 1St IEEE European Symposium on Security and Privacy
-
-
Papernot, N.1
McDaniel, P.2
Jha, S.3
Fredrikson, M.4
Celik, Z.B.5
Swami, A.6
-
29
-
-
85050956856
-
Practical black-box attacks against deep learning systems using adversarial examples
-
Papernot, N., McDaniel, P.D., Goodfellow, I.J., Jha, S., Celik, Z.B., Swami, A.: Practical black-box attacks against deep learning systems using adversarial examples. CoRR, abs/1602.02697 (2016)
-
(2016)
Corr, Abs/1602
, pp. 02697
-
-
Papernot, N.1
McDaniel, P.D.2
Goodfellow, I.J.3
Jha, S.4
Celik, Z.B.5
Swami, A.6
-
30
-
-
77955004015
-
An abstraction-refinement approach to verification of artificial neural networks
-
Touili, T., Cook, B., Jackson, P. (eds.), Springer, Heidelberg
-
Pulina, L., Tacchella, A.: An abstraction-refinement approach to verification of artificial neural networks. In: Touili, T., Cook, B., Jackson, P. (eds.) CAV 2010. LNCS, vol. 6174, pp. 243–257. Springer, Heidelberg (2010). doi:10.1007/978-3-642-14295-6_24
-
(2010)
CAV 2010. LNCS
, vol.6174
, pp. 243-257
-
-
Pulina, L.1
Tacchella, A.2
-
32
-
-
85026730242
-
Towards verification of artificial neural networks
-
Scheibler, K., Winterer, L., Wimmer, R., Becker, B.: Towards verification of artificial neural networks. In: 18th Workshop on Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV), pp. 30–40 (2015)
-
(2015)
18Th Workshop on Methoden Und Beschreibungssprachen Zur Modellierung Und Verifikation Von Schaltungen Und Systemen (MBMV
, pp. 30-40
-
-
Scheibler, K.1
Winterer, L.2
Wimmer, R.3
Becker, B.4
-
33
-
-
85018718411
-
Towards verified artificial intelligence
-
Seshia, S.A., Sadigh, D.: Towards verified artificial intelligence. CoRR, abs/1606.08514 (2016)
-
(2016)
Corr, Abs/1606
, pp. 08514
-
-
Seshia, S.A.1
Sadigh, D.2
-
34
-
-
84933585162
-
Very deep convolutional networks for large-scale image recognition
-
Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556 (2014)
-
(2014)
Arxiv
, vol.1409
, pp. 1556
-
-
Simonyan, K.1
Zisserman, A.2
-
35
-
-
84861783004
-
Man vs. Computer: Benchmark-ingmachine learning algorithms for traffic sign recognition
-
Stallkamp, J., Schlipsing, M., Salmen, J., Igel, C.: Man vs. computer: benchmark-ingmachine learning algorithms for traffic sign recognition. Neural Netw. 32, 323– 332 (2012)
-
(2012)
Neural Netw
, vol.32
-
-
Stallkamp, J.1
Schlipsing, M.2
Salmen, J.3
Igel, C.4
-
36
-
-
85083953343
-
Intriguing properties of neural networks
-
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., Fergus, R.: Intriguing properties of neural networks. In: International Conference on Learning Representations (ICLR-2014) (2014)
-
(2014)
International Conference on Learning Representations (ICLR-2014)
-
-
Szegedy, C.1
Zaremba, W.2
Sutskever, I.3
Bruna, J.4
Erhan, D.5
Goodfellow, I.6
Fergus, R.7
-
37
-
-
0040864988
-
Principles of risk minimization for learning theory
-
Vapnik, V.: Principles of risk minimization for learning theory. In: Advances in Neural Information Processing Systems 4, NIPS Conference, Denver, Colorado, USA, 2–5 December 1991, pp. 831–838 (1991)
-
(1991)
Advances in Neural Information Processing Systems 4, NIPS Conference, Denver, Colorado, USA, 2–5 December 1991
, pp. 831-838
-
-
Vapnik, V.1
-
38
-
-
84986266803
-
Improving the robustness of deep neural networks via stability training
-
CVPR, (2016)
-
Zheng, S., Song, Y., Leung, T., Goodfellow, I.: Improving the robustness of deep neural networks via stability training. In: CVPR 2016 (2016)
-
(2016)
-
-
Zheng, S.1
Song, Y.2
Leung, T.3
Goodfellow, I.4
|