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Awesome-Deep-Learning-Based-Time-Series-Forecasting
1. Time Series Forecasting Papers
- Recurrent Neural Networks for Time Series Forecasting:Current status and future directions paper
- (DSTP-RNN) DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction paper code
- (TPA-LSTM) Temporal Pattern Attention for Multivariate Time Series Forecasting paper code
- Foundations of sequence-to-sequence modeling for time series paper
- (MTNet) A Memory-Network Based Solution for Multivariate Time-Series Forecasting paper code
- (HRHN) Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction paper code
- Conditional Time Series Forecasting with Convolutional Neural Networks paper
- A Multi-Horizon Quantile Recurrent Forecaster paper
- EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction paper
- DeepAR: Probabilistic forecasting with autoregressive recurrent networks paper code
- Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting paper
- Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting paper code
- Adversarial Sparse Transformer for Time Series Forecasting paper
- Deep Rao-Blackwellised Particle Filters for Time Series Forecasting paper
- (DILATE) Shape and Time Distorsion Loss for Training Deep Time Series Forecasting Models paper code
- Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting paper
- High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes paper
- Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting paper
- Deep State Space Models for Time Series Forecasting paper
- Explaining Time Series Predictions With Dynamic Masks
- Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
- Whittle Networks: A Deep Likelihood Model for Time Series
- Neural Rough Differential Equations for Long Time Series
- End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
- Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
- Deep Factors for Forecasting paper
- Autoregressive Convolutional Neural Networks for Asynchronous Time Series paper
- Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series paper
- (LSTNet) Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks paper code
- A Flexible Forecasting Framework for Hierarchical Time Series with Seasonal Patterns: A Case Study of Web Traffic paper
- Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks paper code
- Multi-Horizon Time Series Forecasting with Temporal Attention Learning paper
- Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting paper
- Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series paper
- Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting paper
- Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting paper
- Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting paper
- Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting paper
- Deep State Space Models for Time Series Forecasting paper
- Explainable Deep Neural Networks for Multivariate Time Series Predictions paper
- (GeoMAN) GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction paper code
- (DA-RNN) A Dual-Stage Attention-Based Recurrent Neural Network
for Time Series Prediction paper code
- DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting paper code
- Time Series Prediction with Interpretable Data Reconstruction paper
- Attention-based recurrent neural networks for accurate short-term and long-term dissolved oxygen prediction paper
- Stock Price Prediction Using Attention-based Multi-Input LSTM paper
- Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction paper
- A New Timing Error Cost Function for Binary Time Series Prediction paper
- A bias and variance analysis for multistep-ahead time series forecasting paper
2. Spatial-Temporal Time Series Forecasting Papers
- STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting paper code
- Deep forecast: Deep learning-based spatio-temporal forecasting (2017) paper
- (STFGNN) Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting paper
- (ASTGCN) Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting paper code mxnet
- Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data paper
- Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting paper
- Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction paper
- Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting paper
- Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction paper
- DeepUrbanMomentum: An Online Deep-Learning System for Short-Term Urban Mobility Prediction paper
- Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction paper code
- GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction paper
- Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting paper code-pytorch
- Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data paper
- AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction paper
3. Weather Forecasting Papers
- Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting paper code
- Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction (CVPR2020 PhyDNet) paper code
- Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics (CVPR2019 MIM) paper code
- Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge paper
- PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning (ICML2018) paper code
- PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs (NIPS2017) paper code
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