会议介绍
AAAI的英文全称是 The Association for the Advance of Artificial Intelligence，中文意思是美国人工智能协会。
美国人工智能协会（American Association for Artificial Intelligence）是人工智能领域的主要学术组织之一。该协会主办的年会（AAAI, The National Conference on Artificial Intelligence）是一个主要的人工智能学术会议，被中国计算机协会推荐为A类会议。
今年 AAAI 2021 将于北京时间2021年2月9到12号于线上举行。本次大会共接收了 1692 篇论文，接收率约为21%，可谓收获颇丰。编者梳理与时间序列有关的研究，竟也高达66篇，可见产学两界对该领域的热情与应用前景。完整的接收论文列表可以访问原文获取。
本文梳理AAAI 2021有关时间序列领域的最新研究成果，供大家参考。
- 时间序列
- 预测：4篇
- 分类：4篇
- 异常检测：3篇
- 聚类：1篇
- 补缺：1篇
- 时间关系抽取：3篇
- 时空网络
- 分割：3篇
- 预测：13篇
- 检测：11篇
- 时间知识图谱：3篇
- 时间神经网络：5篇
- 顺序分析
- 推荐：5篇
- 决策：7篇
- 搜索：3篇
时间序列
01
预测
时序预测是时间序列领域的经典问题之一。本次AAAI带来了包括：多维时序预测/分解/多步预测的研究
- Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting
- Dynamic Gaussian Mixture Based Deep Generative Model for Robust Forecasting on Sparse Multivariate Time Series
- Temporal Latent Autoencoder: A Method for Probabilistic Multivariate Time Series Forecasting
- Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting
02
分类
时序分类是时间序列领域的经典问题之一。本次AAAI带来了包括：多维时序分类/标签增强 等研究
- Correlative Channel-Aware Fusion for Multi-View Time Series Classification
- Learnable Dynamic Temporal Pooling for Time Series Classification
- ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification
- Joint-Label Learning by Dual Augmentation for Time Series Classification
03
异常检测
时序异常检测在产业界应用很广。本次AAAI带来了包括：图网络/异常影响等研究
- Graph Neural Network-Based Anomaly Detection in Multivariate Time Series
- Time Series Anomaly Detection with Multiresolution Ensemble Decoding
- Outlier Impact Characterization for Time Series Data
04
聚类
本次AAAI带来了一篇关于不完整时序的聚类研究
- Learning Representations for Incomplete Time Series Clustering
05
补缺
本次AAAI带了一篇关于多维时间序列补缺的研究
- Generative Semi-Supervised Learning for Multivariate Time Series Imputation
时间关系抽取
关系抽取旨在分析不同时序之间相关性，涉及因果推导。本次AAAI带来了3篇研究
- Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference
- Time Series Domain Adaptation via Sparse Associative Structure Alignment
- Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling
时空网络
01
分割
时空分割在视频分段场景应用广泛。本次AAAI带来了3篇研究
- Spatiotemporal Graph Neural Network Based Mask Reconstruction for Video Object Segmentation
- Temporal Relational Modeling with Self-Supervision for Action Segmentation
- Temporal Segmentation of Fine-Gained Semantic Action: A Motion-Centered Figure Skating Dataset
02
预测
时空预测在交通预测，用户行为预测，多因子气象预测等领域应用广泛。本次AAAI带来了13篇研究
- Graph and Temporal Convolutional Network for Spatio-Temporal 3D Multi-Person Pose Estimation in Monocular Videos
- Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning
- BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation
- Automatic Generation of Flexible Plans via Diverse Temporal Planning
- Pre-Training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction
- GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting
- Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting
- Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision
- Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks
- CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-Cloud Stream Forecasting
- Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
- Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network
- FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting
03
检测
时空检测在动作识别，目标检测，事件检测等场景应用广泛。本次AAAI带来了11篇研究
- Spatio-Temporal Difference Descriptor for Skeleton-Based Action Recognition
- Spatial-Temporal Causal Inference for Partial Image-to-Video Adaptation
- Temporal ROI Align for Video Object Recognition
- Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition
- Learning Precise Temporal Point Event Detection with Misaligned Labels
- Real-Time Tropical Cyclone Intensity Estimation by Handling Temporally Heterogeneous Satellite Data
- STELAR: Spatio-Temporal Tensor Factorization with Latent Epidemiological Regularization
- ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization
- Weakly-Supervised Temporal Action Localization by Uncertainty Modeling
- Weakly Supervised Temporal Action Localization through Learning Explicit Subspaces for Action and Context
- A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization
时空知识图谱
时空知识图谱在原有知识图谱上，考虑时间先后的知识变迁。本次AAAI带来3篇研究
- ChronoR: Rotation Based Temporal Knowledge Graph Embedding
- Learning from History: Modeling Temporal Knowledge Graphs with Sequential CopyGeneration Networks
- Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs
时间神经网络
处理时间先后顺序（或序列顺序）的神经网络为时序应用研究提供基础。本次AAAI带来了5篇研究
- Bridging Towers of Multi-Task Learning with a Gating Mechanism for Aspect-Based Sentiment Analysis and Sequential Metaphor Identification
- C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer
- Inductive Graph Neural Networks for Spatiotemporal Kriging
- Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance
- Continuous-Time Attention for Sequential Learning
顺序分析
01
推荐
分析用户购买行为的先后顺序是推荐系统的一大方向。本次AAAI带来了5篇研究
- Cold-Start Sequential Recommendation via Meta Learner
- A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models
- Noninvasive Self-Attention for Side Information Fusion in Sequential Recommendation
- Dynamic Memory Based Attention Network for Sequential Recommendation
- Reinforcement Learning of Sequential Price Mechanisms
02
决策
与推荐类似，用户决策具有一定的先后顺序。本次AAAI带来了7篇研究
- Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games
- Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games
- Sequential Attacks on Kalman Filter-Based Forward Collision Warning Systems
- Apparently Irrational Choice as Optimal Sequential Decision Making
- Ethically Compliant Sequential Decision Making
- Hindsight and Sequential Rationality of Correlated Play
- Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach
03
搜索
如何预估用户的行为从而提高搜索的效率？本次AAAI带来了3篇研究
- When Hashing Met Matching: Efficient Spatio-Temporal Search for Ridesharing
- Synthesis of Search Heuristics for Temporal Planning via Reinforcement Learning
- Sequential End-to-End Network for Efficient Person Search
