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Signature is an infinite graded sequence of statistics known to characterize geometric rough paths, which includes the paths with bounded variation.
Preprint is available at https://arxiv.org/abs/1906.08215
Toth, C., Oberhauser, H.: Bayesian learning from sequential data using Gaussian processes with signature covariances (2019) · 1906
Earlier work this paper cites.
Preprint is available at https://arxiv.org/abs/1908.08286
Liao, S., Lyons, T., Yang, W., Ni, H.: Learning stochastic differential equations using RNN with log signature features (2019) · 1908
Earlier work this paper cites.
Journal of the American Statistical Association 58
Hoeffding, W.: Probability inequalities for sums of bounded random variables · 1963
Earlier work this paper cites.
Econometrica 50
Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation · 1982
Earlier work this paper cites.
Journal of Econometrics 31
Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity · 1986
Earlier work this paper cites.
Cybenko, G. Approximation by superpositions of a sigmoidal function. Mathematics Of Control, Signals And Systems
1989
Earlier work this paper cites.
Neural Networks 2
Funahashi, K.I.: On the approximate realization of continuous mappings by neural networks · 1989
Earlier work this paper cites.
Neural Comput. 9
Hochreiter, S., Schmidhuber, J.: Long short-term memory · 1997
Earlier work this paper cites.
Oxford mathematical monographs. Clarendon Press (2002)
Lyons, T., Qian, Z.: System Control and Rough Paths · 2002
Earlier work this paper cites.
Preprint is available at https://arxiv.org/abs/2006.00873
Morrill, J., Fermanian, A., Kidger, P., Lyons, T.: A generalized signature method for time series (2020) · 2006
Earlier work this paper cites.
MIT press Cambridge, MA (2006)
Williams, C.K., Rasmussen, C.E.: Gaussian processes for machine learning · 2006
Earlier work this paper cites.
In: Differential Equations Driven by Rough Paths: École d’Été de Probabilités de Saint-Flour XXXIV - 2004, Lecture Notes in Mathematics , vol. 1908, pp. 81–93. Springer Berlin Heidelberg (2007)
Lyons, T.J., Caruana, M., Lévy, T.: Differential equations driven by rough paths · 2007
Earlier work this paper cites.
In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp. 142–150. Association for Computational Linguistics, Portland, Oregon, USA (2011)
Maas, A.L., Daly, R.E., Pham, P.T., Huang, D., Ng, A.Y., Potts, C.: Learning word vectors for sentiment analysis · 2011
Earlier work this paper cites.
https://arxiv.org/abs/1307.7244
Gyurkó, L.G., Lyons, T., Kontkowski, M., Field, J.: Extracting information from the signature of a financial data stream (2013) · 2013
Cited alongside, same era.
Preprint is available at https://arxiv.org/abs/1309.0260
Levin, D.A., Lyons, T., Ni, H.: Learning from the past, predicting the statistics for the future, learning an evolving system (2013) · 2013
Cited alongside, same era.
Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., Bengio, Y.: Learning phrase representations using RNN encoder-decoder for statistical machine translation (2014)
2014
Cited alongside, same era.
In: Conference on Empirical Methods in Natural Language Processing (EMNLP 2014) (2014)
Cho, K., van Merrienboer, B., Gulcehre, C., Bougares, F., Schwenk, H., Bengio, Y.: Learning phrase representations using rnn encoder-decoder for statistical machine translation · 2014
Cited alongside, same era.
In: Advances in Neural Information Processing Systems 32, pp. 3105–3115. Curran Associates, Inc. (2019)
Kidger, P., Bonnier, P., Perez Arribas, I., Salvi, C., Lyons, T.: Deep signature transforms · 2019
Later among the works it cites.
Journal of Machine Learning Research 20
Kiraly, F.J., Oberhauser, H.: Kernels for sequentially ordered data · 2019
Later among the works it cites.
Applied Mathematical Finance 26
Lyons, T., Nejad, S., Arribas, I.P.: Numerical method for model-free pricing of exotic derivatives using rough path signatures · 2019
Later among the works it cites.
Available at http://mustafabaydogan.com , [Accessed: 2020-07-12]
Baydogan, M.: Multivariate Time Series Classification Datasets (2015) · 2020
Closest in time.
Data Mining and Knowledge Discovery 34
Dempster, A., Petitjean, F., Webb, G.I.: Rocket: exceptionally fast and accurate time series classification using random convolutional kernels · 2020
Closest in time.
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In: Proceedings of the 2014 International Conference on Big Data Science and Computing, BigDataScience 14. Association for Computing Machinery, New York (2014)
Lyons, T., Ni, H., Oberhauser, H.: A feature set for streams and an application to high-frequency financial tick data · 2014
Cited alongside, same era.
In: Empirical Methods in Natural Language Processing (EMNLP), pp. 1532–1543 (2014)
Pennington, J., Socher, R., Manning, C.D.: Glove: Global vectors for word representation · 2014
Cited alongside, same era.
Advances in Mathematics 293
Boedihardjo, H., Geng, X., Lyons, T., Yang, D.: The signature of a rough path: Uniqueness · 2016
Cited alongside, same era.
Annals of Probability 44
Chevyrev, I., Lyons, T.: Characteristic functions of measures on geometric rough paths · 2016
Cited alongside, same era.
APC 550 Lecture Notes. Princeton University (2016)
van Handel, R.: Probability in High Dimension · 2016
Cited alongside, same era.
In: I. Guyon, U.V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (eds.) Advances in Neural Information Processing Systems, vol. 30. Curran Associates, Inc. (2017)
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need · 2017
Cited alongside, same era.
Preprint is available at https://arxiv.org/abs/1809.09466
Arribas, I.P.: Derivatives pricing using signature payoffs (2018) · 2018
Cited alongside, same era.
SIAM Journal on Scientific Computing 40
Raissi, M., Perdikaris, P., Karniadakis, G.E.: Numerical Gaussian processes for time-dependent and non-linear partial differential equations · 2018
Cited alongside, same era.
2020
Closest in time.
Preprint is available at arXiv:2001.00706 (2020)
Kidger, P., Lyons, T.: Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU · 2020
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Applied Mathematical Finance 27
Lyons, T., Nejad, S., Arribas, I.P.: Non-parametric pricing and hedging of exotic derivatives · 2020
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Stochastic Processes and their Applications 130
Detering, N., Fouque, J.P., Ichiba, T.: Directed chain stochastic differential equations · 2021
Closest in time.
Min, M. & Hu, R. Signatured Deep Fictitious Play for Mean Field Games with Common Noise. Proceedings Of The 38th International Conference On Machine Learning
2021
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Data Mining and Knowledge Discovery 35
Ruiz, A.P., Flynn, M., Large, J., Middlehurst, M., Bagnall, A.: The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances · 2021
Closest in time.
SIAM J. Math. Data Sci. 3
Salvi, C. and Cass, T. and Foster, J. and Lyons, T., Yang, W.: The Signature Kernel Is the Solution of a Goursat PDE · 2021
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