2021年三大顶会时间序列论文&代码整理
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
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
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
Temporal Latent Autoencoder: A Method for Probabilistic Multivariate Time Series Forecasting
下载：https://arxiv.org/abs/2101.10460
代码：未找到
Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting
下载：https://arxiv.org/abs/2102.00431
代码：未找到
Correlative Channel-Aware Fusion for Multi-View Time Series Classification
下载：https://arxiv.org/abs/1911.11561
代码：未找到
Learnable Dynamic Temporal Pooling for Time Series Classification
下载：https://arxiv.org/abs/2104.02577
代码：https://github.com/donalee/DTW-Pool
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
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
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
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
Outlier Impact Characterization for Time Series Data
下载：https://ojs.aaai.org/index.php/AAAI/article/view/17379
代码：未找到
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
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
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
Inductive Graph Neural Networks for Spatiotemporal Kriging
下载：https://arxiv.org/abs/2006.07527
代码：https://github.com/Kaimaoge/IGNNK
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
Continuous-Time Attention for Sequential Learning
下载：https://ojs.aaai.org/index.php/AAAI/article/view/16875
代码：未找到
ChronoR: Rotation Based Temporal Knowledge Graph Embedding
下载：https://arxiv.org/abs/2103.10379
代码：未找到
Learning from History: Modeling Temporal Knowledge Graphs with Sequential CopyGeneration Networks
下载：https://arxiv.org/abs/2012.08492
代码：未找到
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
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
下载：https://arxiv.org/abs/2106.09296
代码：https://github.com/huckiyang/Voice2Series-Reprogramming
Neural Rough Differential Equations for Long Time Series
下载：https://arxiv.org/abs/2009.08295
代码：https://github.com/jambo6/neuralRDEs
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
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
下载：https://arxiv.org/abs/2101.12072
代码：未找到
Conformal prediction interval for dynamic time-series
下载：https://arxiv.org/abs/2010.09107
代码：https://github.com/hamrel-cxu/EnbPI
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
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
Approximation Theory of Convolutional Architectures for Time Series Modelling
下载：http://proceedings.mlr.press/v139/jiang21d/jiang21d.pdf
代码：未找到
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
Explaining Time Series Predictions with Dynamic Masks
下载：https://arxiv.org/abs/2106.05303
代码：https://github.com/JonathanCrabbe/Dynamask
ST-DETR: Spatio-Temporal Object Traces Attention Detection Transformer
- 下载：https://arxiv.org/pdf/2107.05887.pdf
- 代码：未找到Temporal Dependencies in Feature Importance for Time Series Predictions
下载：https://arxiv.org/abs/2107.14317
代码：未找到
IJCAI
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
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
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
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
Time Series Data Augmentation for Deep Learning: A Survey
下载：https://arxiv.org/abs/2002.12478
代码：无
Uncertain Time Series Classification
下载：https://www.ijcai.org/proceedings/2021/0683.pdf
代码：https://github.com/frankl1/ustc
Learning Temporal Causal Sequence Relationships from Real-Time Time-
下载：https://arxiv.org/abs/1905.12262
代码：未找到
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
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
https://www.yanxishe.com/reportDetail/26029
https://icml.cc/Conferences/2021/Schedule?type=Poster
https://ijcai-21.org/program-main-track/
https://dreamhomes.top/posts/202108241839/
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