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2021年三大顶会时间序列论文&代码整理

机器学习初学者

共 6408字，需浏览 13分钟

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2021-10-26 00:06

作者：杰少，炼丹笔记嘉宾

2021年最新时间序列预测论文&代码整理

AAAI 2021

  1. Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting

    • 下载：https://arxiv.org/abs/2009.05135

    • 代码：https://github.com/ostadabbas/DSARF

  2. Dynamic Gaussian Mixture Based Deep Generative Model for Robust Forecasting on Sparse Multivariate Time Series

    • 下载：https://arxiv.org/abs/2103.02164

    • 代码：https://paperswithcode.com/paper/dynamic-gaussian-mixture-based-deep#code

  3. Temporal Latent Autoencoder: A Method for Probabilistic Multivariate Time Series Forecasting

    • 下载：https://arxiv.org/abs/2101.10460

    • 代码：未找到

  4. Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

    • 下载：https://arxiv.org/abs/2102.00431

    • 代码：未找到

  5. Correlative Channel-Aware Fusion for Multi-View Time Series Classification

    • 下载：https://arxiv.org/abs/1911.11561

    • 代码：未找到

  6. Learnable Dynamic Temporal Pooling for Time Series Classification

    • 下载：https://arxiv.org/abs/2104.02577

    • 代码：https://github.com/donalee/DTW-Pool

  7. ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17018

    • 代码：未找到

  8. Joint-Label Learning by Dual Augmentation for Time Series Classification

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17071

    • 代码：未找到

  9. Graph Neural Network-Based Anomaly Detection in Multivariate Time Series

    • 下载：https://arxiv.org/abs/2106.06947

    • 代码：https://github.com/d-ailin/GDN

  10. Time Series Anomaly Detection with Multiresolution Ensemble Decoding

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17152

    • 代码：未找到

  11. Outlier Impact Characterization for Time Series Data

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17379

    • 代码：未找到

  12. Generative Semi-Supervised Learning for Multivariate Time Series Imputation

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17086

    • 代码：https://githubmemory.com/repo/zjuwuyy-DL/Generative-Semi-supervised-Learning-for-Multivariate-Time-Series-Imputation

  13. Bridging Towers of Multi-Task Learning with a Gating Mechanism for Aspect-Based Sentiment Analysis and Sequential Metaphor Identification

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17596

    • 代码：未找到

  14. C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer

    • 下载：https://arxiv.org/abs/2012.08976

    • 代码：https://github.com/wswdx/C2F-FWN

  15. Inductive Graph Neural Networks for Spatiotemporal Kriging

    • 下载：https://arxiv.org/abs/2006.07527

    • 代码：https://github.com/Kaimaoge/IGNNK

  16. Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/17329

    • 代码：https://github.com/zbs881314/Temporal-Coded-Deep-SNN

  17. Continuous-Time Attention for Sequential Learning

    • 下载：https://ojs.aaai.org/index.php/AAAI/article/view/16875

    • 代码：未找到

  18. ChronoR: Rotation Based Temporal Knowledge Graph Embedding

    • 下载：https://arxiv.org/abs/2103.10379

    • 代码：未找到

  19. Learning from History: Modeling Temporal Knowledge Graphs with Sequential CopyGeneration Networks

    • 下载：https://arxiv.org/abs/2012.08492

    • 代码：未找到

  20. Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs

    • 下载：https://arxiv.org/abs/1911.11455

    • 代码：未找到

ICML 2021

  1. Voice2Series: Reprogramming Acoustic Models for Time Series Classification

    • 下载：https://arxiv.org/abs/2106.09296

    • 代码：https://github.com/huckiyang/Voice2Series-Reprogramming

  2. Neural Rough Differential Equations for Long Time Series

    • 下载：https://arxiv.org/abs/2009.08295

    • 代码：https://github.com/jambo6/neuralRDEs

  3. Necessary and sufficient conditions for causal feature selection in time series with latent common causes

    • 下载：https://arxiv.org/abs/2005.08543

    • 代码：未找到

  4. Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

    • 下载：https://arxiv.org/abs/2101.12072

    • 代码：未找到

  5. Conformal prediction interval for dynamic time-series

    • 下载：https://arxiv.org/abs/2010.09107

    • 代码：https://github.com/hamrel-cxu/EnbPI

  6. Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting

    • 下载：https://arxiv.org/abs/2105.04100

    • 代码：https://github.com/Z-GCNETs/Z-GCNETs

  7. End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series

    • 下载：https://proceedings.mlr.press/v139/rangapuram21a.html

    • 代码：https://github.com/awslabs/gluon-ts

  8. Approximation Theory of Convolutional Architectures for Time Series Modelling

    • 下载：http://proceedings.mlr.press/v139/jiang21d/jiang21d.pdf

    • 代码：未找到

  9. Whittle Networks: A Deep Likelihood Model for Time Series

    • 下载：http://proceedings.mlr.press/v139/yu21c.html

    • 代码：https://github.com/ml-research/WhittleNetworks

  10. Explaining Time Series Predictions with Dynamic Masks

    • 下载：https://arxiv.org/abs/2106.05303

    • 代码：https://github.com/JonathanCrabbe/Dynamask

  11. ST-DETR: Spatio-Temporal Object Traces Attention Detection Transformer

- 下载：https://arxiv.org/pdf/2107.05887.pdf

- 代码：未找到

  1. Temporal Dependencies in Feature Importance for Time Series Predictions

    • 下载：https://arxiv.org/abs/2107.14317

    • 代码：未找到

IJCAI

  1. Time-Aware Multi-Scale RNNs for Time Series Modeling

    • 下载：https://www.ijcai.org/proceedings/2021/315

    • 代码：https://github.com/qianlima-lab/TAMS-RNNs

  2. Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting

    • 下载：https://www.ijcai.org/proceedings/2021/397

    • 代码：未找到

  3. TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data

    • 下载：https://arxiv.org/abs/2105.00412

    • 代码：未找到

  4. Time-Series Representation Learning via Temporal and Contextual Contrasting

    • 下载：https://arxiv.org/abs/2106.14112

    • 代码：https://github.com/emadeldeen24/TS-TCC

  5. Time Series Data Augmentation for Deep Learning: A Survey

    • 下载：https://arxiv.org/abs/2002.12478

    • 代码：无

  6. Uncertain Time Series Classification

    • 下载：https://www.ijcai.org/proceedings/2021/0683.pdf

    • 代码：https://github.com/frankl1/ustc

  7. Learning Temporal Causal Sequence Relationships from Real-Time Time-

    • 下载：https://arxiv.org/abs/1905.12262

    • 代码：未找到

  8. Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation

    • 下载：https://www.ijcai.org/proceedings/2021/378

    • 代码：https://github.com/jarheadjoe/Adv-spec-ker-matching

  9. Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling

    • 下载：https://www.ijcai.org/proceedings/2021/493

    • 代码：未找到

参考文献

  1. https://www.yanxishe.com/reportDetail/26029

  2. https://icml.cc/Conferences/2021/Schedule?type=Poster

  3. https://ijcai-21.org/program-main-track/

  4. https://dreamhomes.top/posts/202108241839/


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