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In the realm of time series forecasting (TSF), it is imperative for models to adeptly discern and distill hidden patterns within historical time series data to forecast future states.
The fourier transform
Bracewell, R.N., 1989 · 1989
Earlier work this paper cites.
Transformers-Based Encoder Model for Forecasting Hourly Power Output of Transparent Photovoltaic Module Systems
Sherozbek, J., Park, J., Akhtar, M.S., Yang, O.B., 2023 · 1996
Earlier work this paper cites.
Freeway performance measurement system: mining loop detector data
Chen, C., Petty, K., Skabardonis, A., Varaiya, P., Jia, Z., 2001 · 2001
Earlier work this paper cites.
Reformer: The efficient transformer
Kitaev, N., Kaiser, Ł., Levskaya, A., 2020 · 2001
Earlier work this paper cites.
Recurrent neural networks
Medsker, L.R., Jain, L., et al., 2001 · 2001
Earlier work this paper cites.
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey
Benidis, K., Rangapuram, S.S., Flunkert, V., Wang, Y., Maddix, D., Turkmen, C., Gasthaus, J., Bohlke-Schneider, M., Salinas, D., Stella, L., Aubet, F.X., Callot, L., Januschowski, T., 2023 · 2004
Earlier work this paper cites.
25 years of time series forecasting
De Gooijer, J.G., Hyndman, R.J., 2006 · 2006
Earlier work this paper cites.
Hippo: Recurrent memory with optimal polynomial projections
Gu, A., Dao, T., Ermon, S., Rudra, A., Ré, C., 2020 · 2008
Earlier work this paper cites.
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Elfwing, S., Uchibe, E., Doya, K., 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I., 2017 · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.W., Lee, K., Toutanova, K., 2018 · 2018
Earlier work this paper cites.
Modeling long-and short-term temporal patterns with deep neural networks, in: The 41st international ACM SIGIR conference on research & development in information retrieval, pp. 95–104
Lai, G., Chang, W.C., Yang, Y., Liu, H., 2018 · 2018
Earlier work this paper cites.
Deep state space models for time series forecasting
Rangapuram, S.S., Seeger, M.W., Gasthaus, J., Stella, L., Wang, Y., Januschowski, T., 2018 · 2018
Earlier work this paper cites.
Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting
Li, S., Jin, X., Xuan, Y., Zhou, X., Chen, W., Wang, Y.X., Yan, X., 2019 · 2019
Earlier work this paper cites.
Financial time series forecasting with deep learning : A systematic literature review: 2005–2019
Sezer, O.B., Gudelek, M.U., Ozbayoglu, A.M., 2020 · 2020
Earlier work this paper cites.
Time-series forecasting with deep learning: a survey
Lim, B., Zohren, S., 2021 · 2021
Earlier work this paper cites.
A Survey on Deep Learning for Time-Series Forecasting. Springer International Publishing, Cham
Mahmoud, A., Mohammed, A., 2021 · 2021
Earlier work this paper cites.
Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Wu, H., Xu, J., Wang, J., Long, M., 2021 · 2021
Earlier work this paper cites.
Informer: Beyond efficient transformer for long sequence time-series forecasting, in: Proceedings of the AAAI conference on artificial intelligence, pp. 11106–11115
Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., Zhang, W., 2021 · 2021
Earlier work this paper cites.
A New Transformer-Based Hybrid Model for Forecasting Crude Oil Returns
Abdollah Pour, M.M., Hajizadeh, E., Farineya, P., 2022 · 2022
Earlier work this paper cites.
Flashattention: Fast and memory-efficient exact attention with io-awareness
Dao, T., Fu, D., Ermon, S., Rudra, A., Ré, C., 2022 · 2022
Earlier work this paper cites.
Scinet: Time series modeling and forecasting with sample convolution and interaction
Liu, M., Zeng, A., Chen, M., Xu, Z., Lai, Q., Ma, L., Xu, Q., 2022 · 2022
Cited alongside, same era.
Transformers-based time series forecasting for piezometric level prediction, in: 2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), pp. 1–6
Mellouli, N., Rabah, M.L., Farah, I.R., 2022 · 2022
Cited alongside, same era.
A time series is worth 64 words: Long-term forecasting with transformers, in: The Eleventh International Conference on Learning Representations
Nie, Y., Nguyen, N.H., Sinthong, P., Kalagnanam, J., 2022 · 2022
Cited alongside, same era.
Simplified state space layers for sequence modeling
Smith, J.T., Warrington, A., Linderman, S.W., 2022 · 2022
Cited alongside, same era.
ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
Blackmamba: Mixture of experts for state-space models
Anthony, Q., Tokpanov, Y., Glorioso, P., Millidge, B., 2024 · 2024
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Hierarchical state space models for continuous sequence-to-sequence modeling
Bhirangi, R., Wang, C., Pattabiraman, V., Majidi, C., Gupta, A., Hellebrekers, T., Pinto, L., 2024 · 2024
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A novel state space model with local enhancement and state sharing for image fusion
Cao, Z., Wu, X., Deng, L.J., Zhong, Y., 2024 · 2024
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MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection
Chen, T., Tan, Z., Gong, T., Chu, Q., Wu, Y., Liu, B., Ye, J., Yu, N., 2024 · 2024
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Woo, G., Liu, C., Sahoo, D., Kumar, A., Hoi, S., 2022 · 2022
Cited alongside, same era.
Are transformers effective for time series forecasting?, in: AAAI Conference on Artificial Intelligence
Zeng, A., Chen, M.H., Zhang, L., Xu, Q., 2022 · 2022
Cited alongside, same era.
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
Zhang, T., Zhang, Y., Cao, W., Bian, J., Yi, X., Zheng, S., Li, J., 2022 · 2022
Cited alongside, same era.
Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting, in: The eleventh international conference on learning representations
Zhang, Y., Yan, J., 2022 · 2022
Cited alongside, same era.
Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting, in: International conference on machine learning, PMLR. pp. 27268–27286
Zhou, T., Ma, Z., Wen, Q., Wang, X., Sun, L., Jin, R., 2022 · 2022
Cited alongside, same era.
Transformers in Time-series Analysis: A Tutorial
Ahmed, S., Nielsen, I.E., Tripathi, A., Siddiqui, S., Rasool, G., Ramachandran, R.P., 2023 · 2023
Cited alongside, same era.
A survey on evaluation of large language models
Chang, Y., Wang, X., Wang, J., Wu, Y., Yang, L., Zhu, K., Chen, H., Yi, X., Wang, C., Wang, Y., et al., 2023 · 2023
Cited alongside, same era.
TSMixer: An All-MLP Architecture for Time Series Forecasting
Chen, S.A., Li, C.L., Yoder, N., Arik, S.O., Pfister, T., 2023 · 2023
Cited alongside, same era.
Dong, W., Zhu, H., Lin, S., Luo, X., Shen, Y., Liu, X., Zhang, J., Guo, G., Zhang, B., 2024 · 2024
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Improving position encoding of transformers for multivariate time series classification
Foumani, N.M., Tan, C.W., Webb, G.I., Salehi, M., 2024 · 2024
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Is mamba capable of in-context learning?
Grazzi, R., Siems, J., Schrodi, S., Brox, T., Hutter, F., 2024 · 2024
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Huang, J., Yang, L., Wang, F., Wu, Y., Nan, Y., Aviles-Rivero, A.I., Schönlieb, C.B., Zhang, D., Yang, G., 2024 · 2024
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Jiang, X., Han, C., Mesgarani, N., 2024 · 2024
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VideoMamba: State Space Model for Efficient Video Understanding
Li, K., Li, X., Wang, Y., He, Y., Wang, Y., Wang, L., Qiao, Y., 2024 · 2024
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Hsidmamba: Exploring bidirectional state-space models for hyperspectral denoising
Liu, Y., Xiao, J., Guo, Y., Jiang, P., Yang, H., Wang, F., 2024 · 2024
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U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation
Ma, J., Li, F., Wang, B., 2024 · 2024
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MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
Pióro, M., Ciebiera, K., Król, K., Ludziejewski, J., Krutul, M., Krajewski, J., Antoniak, S., Miłoś, P., Cygan, M., Jaszczur, S., 2024 · 2024
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Caduceus: Bi-directional equivariant long-range dna sequence modeling
Schiff, Y., Kao, C.H., Gokaslan, A., Dao, T., Gu, A., Kuleshov, V., 2024 · 2024
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Mambastock: Selective state space model for stock prediction
Shi, Z., 2024 · 2024
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A lightweight multi-layer perceptron for efficient multivariate time series forecasting
Wang, Z., Ruan, S., Huang, T., Zhou, H., Zhang, S., Wang, Y., Wang, L., Huang, Z., Liu, Y., 2024b · 2024
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Spectralmamba: Efficient mamba for hyperspectral image classification
Yao, J., Hong, D., Li, C., Chanussot, J., 2024 · 2024
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Medmamba: Vision mamba for medical image classification
Yue, Y., Li, Z., 2024 · 2024
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Cobra: Extending mamba to multi-modal large language model for efficient inference
Zhao, H., Zhang, M., Zhao, W., Ding, P., Huang, S., Wang, D., 2024 · 2024
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Vision mamba: Efficient visual representation learning with bidirectional state space model
Zhu, L., Liao, B., Zhang, Q., Wang, X., Liu, W., Wang, X., 2024 · 2024
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