Modern Machine Learning Methods for Time Series Analysis

Long Short-Term Memory

Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318 · see citing works

Deep learning

LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works

Learning representations by back-propagating errors

Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892 · see citing works

Multilayer feedforward networks are universal approximators

Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728 · see citing works

Deep learning in neural networks: an overview

Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works

A logical calculus of the ideas immanent in nervous activity

McCulloch, W. S., & Pitts, W. (1943) · The Bulletin of Mathematical Biophysics · doi:10.1007/bf02478259 · Cited by 18,566 · see citing works

A fast learning algorithm for deep belief nets

Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336 · see citing works

I.—COMPUTING MACHINERY AND INTELLIGENCE

TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · see citing works

Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

Fukushima, K. (1980) · Biological Cybernetics · doi:10.1007/bf00344251 · Cited by 5,759 · see citing works

Forecasting with artificial neural networks:

Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229 · see citing works

A learning algorithm for Boltzmann machines

Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. (1985) · Cognitive Science · doi:10.1207/s15516709cog0901_7 · Cited by 3,402 · see citing works

Deep learning for time series classification: a review

Ismail Fawaz, H., Forestier, G., Weber, J., Idoumghar, L., & Muller, P.-A. (2019) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-019-00619-1 · Cited by 3,342 · see citing works

Theory of the backpropagation neural network

Hecht-Nielsen (1989) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.1989.118638 · Cited by 2,221 · see citing works

Time-series forecasting with deep learning: a survey

Lim, B. Y., & Zohren, S. (2021) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0209 · Cited by 1,976 · see citing works

Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

Hong, T., Pinson, P., Shu, F., Zareipour, H., Troccoli, A., & Hyndman, R. J. (2016) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2016.02.001 · Cited by 1,068 · see citing works

Applied optimal control: Optimization, estimation, and control

Tsypkin, Y. Ζ. (1970) · Automatica · doi:10.1016/0005-1098(70)90033-6 · Cited by 959 · see citing works

Neural Networks and Deep Learning

Aggarwal, C. (2018) · Cambridge International Law Journal · doi:10.1007/978-3-319-94463-0 · Cited by 932 · see citing works

Deep Learning for Time Series Forecasting: A Survey

Torres, J. F., Hadjout, D., Sebaa, A., Alvarez, F. M., & Troncoso, A. (2020) · Big Data · doi:10.1089/big.2020.0159 · Cited by 847 · see citing works

Deep State Space Models for Time Series Forecasting

Rangapuram, S. S., Seeger, M., Gasthaus, J. A., Stella, L., Wang, Y., & Januschowski, T. (2018) · neural information processing systems · Cited by 500 · see citing works

The Deep Learning Revolution

Sejnowski, T. J. (2018) · doi:10.7551/mitpress/11474.001.0001 · Cited by 438 · see citing works

Learning Complex, Extended Sequences Using the Principle of History Compression

Schmidhuber, J. (1992) · Neural Computation · doi:10.1162/neco.1992.4.2.234 · Cited by 398 · see citing works

The quest for artificial intelligence: a history of ideas and achievements

(2010) · Choice Reviews Online · doi:10.5860/choice.47-5695 · Cited by 307 · see citing works

A Selective Overview of Deep Learning

Fan, J., Ma, C., & Zhong, Y. (2021) · Statistical Science · doi:10.1214/20-sts783 · Cited by 181 · see citing works

Time Series Clustering and Classification

Maharaj, E. A., D’Urso, P., & Caiado, J. (2019) · Chapman & Hall/CRC eBooks · doi:10.1201/9780429058264 · Cited by 123 · see citing works

Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions

Chen, S., Yu, J., Chamouni, S., Wang, Y., & Li, Y. (2024) · BMC Medicine · doi:10.1186/s12916-024-03566-x · Cited by 73 · see citing works

A Survey on Deep Learning Models Embed Bio-Inspired Algorithms in Cardiac Disease Classification

Pandiyan, N., & Narayan, S. (2022) · The Open Biomedical Engineering Journal · doi:10.2174/18741207-v16-e221227-2022-ht27-3589-14 · Cited by 4 · see citing works

Efficient Disease Risk Prediction based on Deep Learning Approach

Lalithadevi, B., & Krishnaveni, S. (2022) · International Conference on Computing Methodologies and Communication (ICCMC) · doi:10.1109/iccmc53470.2022.9753851 · Cited by 10 · see citing works

A Comprehensive Analysis of Machine Learning Techniques in Biomedical Image Processing Using Convolutional Neural Network

Shrivastava, A., Chakkaravathy, M., & Shah, M. A. (2022) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i56241.2022.10072911 · Cited by 27 · see citing works

Machine Learning and Deep Learning applications-a vision using the SPSS Method

Bhagwandas, K. K. (2020) · doi:10.46632/rmc/1/3/3

Optimization of Machine Learning and Deep Learning Algorithms for Diagnosis of Cancer

Hari Krishna, D., Anand, M., Saravanan, D., et al. (2022) · ECS Transactions · doi:10.1149/10701.9389ecst · Cited by 6 · see citing works