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[1] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[2] Yang Yang,et al. Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets , 2019, AAAI.
[3] Razvan Pascanu,et al. A simple neural network module for relational reasoning , 2017, NIPS.
[4] Andrew Zisserman,et al. Learning and Using the Arrow of Time , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[5] Ali Etemad,et al. Self-Supervised Learning for ECG-Based Emotion Recognition , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[6] Jason Lines,et al. Classification of time series by shapelet transformation , 2013, Data Mining and Knowledge Discovery.
[7] Jason Lines,et al. Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles , 2015, IEEE Trans. Knowl. Data Eng..
[8] Nikos Komodakis,et al. Unsupervised Representation Learning by Predicting Image Rotations , 2018, ICLR.
[9] Geoffrey E. Hinton,et al. A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.
[10] Micah B. Goldwater,et al. Relational Discovery in Category Learning , 2018, Journal of experimental psychology. General.
[11] Tomasz Górecki,et al. Non-isometric transforms in time series classification using DTW , 2014, Knowl. Based Syst..
[12] Danqi Chen,et al. Reasoning With Neural Tensor Networks for Knowledge Base Completion , 2013, NIPS.
[13] Li Fei-Fei,et al. CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Yoshua Bengio,et al. Learning deep representations by mutual information estimation and maximization , 2018, ICLR.
[15] Razvan Pascanu,et al. Relational inductive biases, deep learning, and graph networks , 2018, ArXiv.
[16] Satya Narayan Shukla,et al. Interpolation-Prediction Networks for Irregularly Sampled Time Series , 2019, ICLR.
[17] Abhinav Gupta,et al. Unsupervised Learning of Visual Representations Using Videos , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[18] Romain Tavenard,et al. Data Augmentation for Time Series Classification using Convolutional Neural Networks , 2016 .
[19] Johan Lukkien,et al. Multi-task Self-Supervised Learning for Human Activity Detection , 2019, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..
[20] Hsiang-Fu Yu,et al. Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting , 2019, NeurIPS.
[21] Yoshua Bengio,et al. Multi-Task Self-Supervised Learning for Robust Speech Recognition , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[22] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[23] Jianbo Jiao,et al. Self-supervised Video Representation Learning by Pace Prediction , 2020, ECCV.
[24] Qianli Ma,et al. Triple-Shapelet Networks for Time Series Classification , 2019, 2019 IEEE International Conference on Data Mining (ICDM).
[25] Eamonn J. Keogh,et al. Time series shapelets: a new primitive for data mining , 2009, KDD.
[26] Shibin Wang,et al. Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study , 2020, ISA transactions.
[27] Alexei A. Efros,et al. Context Encoders: Feature Learning by Inpainting , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Seiichi Uchida,et al. Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative Teacher , 2020, 2020 25th International Conference on Pattern Recognition (ICPR).
[29] Myeongsu Kang,et al. Time-Varying and Multiresolution Envelope Analysis and Discriminative Feature Analysis for Bearing Fault Diagnosis , 2015, IEEE Transactions on Industrial Electronics.
[30] Charles Kemp,et al. The discovery of structural form , 2008, Proceedings of the National Academy of Sciences.
[31] Jason Lines,et al. Time series classification with ensembles of elastic distance measures , 2015, Data Mining and Knowledge Discovery.
[32] Paolo Favaro,et al. Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles , 2016, ECCV.
[33] G Deco,et al. Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep , 2019, Nature Communications.
[34] Martial Hebert,et al. Shuffle and Learn: Unsupervised Learning Using Temporal Order Verification , 2016, ECCV.
[35] Razvan Pascanu,et al. Deep reinforcement learning with relational inductive biases , 2018, ICLR.
[36] Graham W. Taylor,et al. Improved Regularization of Convolutional Neural Networks with Cutout , 2017, ArXiv.
[37] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[38] Nicolas Chapados,et al. N-BEATS: Neural basis expansion analysis for interpretable time series forecasting , 2019, ICLR.
[39] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[40] Donald J. Berndt,et al. Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.
[41] George C. Runger,et al. A Bag-of-Features Framework to Classify Time Series , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[42] Houshang Darabi,et al. LSTM Fully Convolutional Networks for Time Series Classification , 2017, IEEE Access.
[43] Dana Kulic,et al. Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks , 2017, ICMI.
[44] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[45] Yoshua Bengio,et al. Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks , 2019, INTERSPEECH.
[46] Martin Jaggi,et al. Unsupervised Scalable Representation Learning for Multivariate Time Series , 2019, NeurIPS.
[47] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[48] Flora D. Salim,et al. Federated Self-Supervised Learning of Multisensor Representations for Embedded Intelligence , 2020, IEEE Internet of Things Journal.
[49] Bolei Zhou,et al. Temporal Relational Reasoning in Videos , 2017, ECCV.
[50] Ronan Collobert,et al. wav2vec: Unsupervised Pre-training for Speech Recognition , 2019, INTERSPEECH.
[51] Amos Storkey,et al. Self-Supervised Relational Reasoning for Representation Learning , 2020, NeurIPS.
[52] Patrick Schäfer. The BOSS is concerned with time series classification in the presence of noise , 2014, Data Mining and Knowledge Discovery.