On the public citation graph
MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-540-28645-5_29openalex-snapshot
Learning with Drift Detection
inferredcites →https://doi.org/10.1007/s10994-019-05815-0openalex-snapshot
Temporal pattern attention for multivariate time series forecasting
inferredcites →https://doi.org/10.1007/s10994-019-05835-wopenalex-snapshot
Handling concept drift via model reuse
inferredcites →https://doi.org/10.1007/s12530-016-9168-2openalex-snapshot
Discussion and review on evolving data streams and concept drift adapting
inferredcites →https://doi.org/10.1016/b978-012088469-8.50019-xopenalex-snapshot
Detecting Change in Data Streams
inferredcites →https://doi.org/10.1023/a:1018046501280openalex-snapshot
Learning in the Presence of Concept Drift and Hidden Contexts
inferredcites →https://doi.org/10.1038/nature07850openalex-snapshot
Understanding individual human mobility patterns
inferredcites →https://doi.org/10.1109/jsait.2020.2991561openalex-snapshot
The Information Bottleneck Problem and its Applications in Machine Learning
inferredcites →https://doi.org/10.1109/tits.2019.2935152openalex-snapshot
T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction
inferredcites →https://doi.org/10.1109/tits.2019.2950416openalex-snapshot
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
inferredcites →https://doi.org/10.1109/tkde.2021.3077056openalex-snapshot
DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction
inferredcites →https://doi.org/10.1137/1.9781611972771.42openalex-snapshot
Learning from Time-Changing Data with Adaptive Windowing
inferredcites →https://doi.org/10.1145/2623330.2623628openalex-snapshot
Prediction of human emergency behavior and their mobility following large-scale disaster
inferredcites →https://doi.org/10.1145/3209978.3210006openalex-snapshot
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
inferredcites →https://doi.org/10.1145/3380986openalex-snapshot
Dynamic Public Resource Allocation Based on Human Mobility Prediction
inferredcites →https://doi.org/10.1145/3394486.3403118openalex-snapshot
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
inferredcites →https://doi.org/10.1145/3459637.3482000openalex-snapshot
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction
inferredcites →https://doi.org/10.1145/3485447.3512221openalex-snapshot
MemStream: Memory-Based Streaming Anomaly Detection
inferredcites →https://doi.org/10.1145/3543507.3583991openalex-snapshot
Learning Social Meta-knowledge for Nowcasting Human Mobility in Disaster
inferredcites →https://doi.org/10.1609/aaai.v31i1.10735openalex-snapshot
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
inferredcites →https://doi.org/10.1609/aaai.v32i1.11836openalex-snapshot
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015668openalex-snapshot
Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction
inferredcites →https://doi.org/10.1609/aaai.v33i01.3301922openalex-snapshot
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting
inferredcites →https://doi.org/10.1609/aaai.v34i01.5477openalex-snapshot
GMAN: A Graph Multi-Attention Network for Traffic Prediction
inferredcites →https://doi.org/10.1609/aaai.v36i4.20327openalex-snapshot
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
inferredcites →https://doi.org/10.1609/aaai.v36i4.20342openalex-snapshot
Event-Aware Multimodal Mobility Nowcasting
inferredcites →https://doi.org/10.1609/aaai.v37i6.25914openalex-snapshot
Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting
inferredcites →https://doi.org/10.1609/aaai.v37i7.25976openalex-snapshot
Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
inferredcites →https://doi.org/10.24963/ijcai.2018/505openalex-snapshot
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
inferredcites →https://doi.org/10.24963/ijcai.2019/264openalex-snapshot
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.48550/arxiv.1801.04062openalex-snapshot
MINE: Mutual Information Neural Estimation
inferredcites →https://doi.org/10.48550/arxiv.2001.02908openalex-snapshot
Spatial-Temporal Transformer Networks for Traffic Flow Forecasting
inferredcites →https://doi.org/10.48550/arxiv.2007.02842openalex-snapshot
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
inferredcites →https://doi.org/10.48550/arxiv.2108.04443openalex-snapshot
AdaRNN: Adaptive Learning and Forecasting of Time Series
inferredcites →https://doi.org/10.48550/arxiv.physics/0004057openalex-snapshot
The information bottleneck method
inferredcites →https://doi.org/10.52202/068431-0718openalex-snapshot
Non-Stationary Transformers: Exploring the Stationarity in Time Series Forecasting
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4886773openalex-extracted
De-Noising is All You Need: An Svd-Based Method to Enhance the Performance of Graph Neural Networks in Traffic Flow Prediction
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.125053openalex-snapshot
ST-TDCN: A two-channel tree-structure spatial–temporal convolutional network model for traffic velocity prediction
inferred← citeshttps://doi.org/10.1109/tevc.2025.3589643openalex-snapshot
Data-Driven Evolutionary Computation Under Continuously Streaming Environments: A Drift-Aware Approach
inferred← citeshttps://doi.org/10.1109/tits.2025.3588867openalex-snapshot
MM-STFlowNet: A Transportation Hub-Oriented Multi-Mode Passenger Flow Prediction Method via Spatial-Temporal Dynamic Graph Modeling
inferred← citeshttps://doi.org/10.1109/tits.2026.3686236openalex-snapshot
Bridging Temporal Gaps: A Distribution Shift-Aware Approach for Long-Term Data Utilization in Short-Term Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tkde.2025.3536009openalex-snapshot
CLEAR: Spatial-Temporal Traffic Data Representation Learning for Traffic Prediction
inferred← citeshttps://doi.org/10.1145/3627673.3679757openalex-snapshot
Scalable Transformer for High Dimensional Multivariate Time Series Forecasting
inferred← citeshttps://doi.org/10.1145/3660523openalex-snapshot
Overcoming Catastrophic Forgetting in Continual Fine-Grained Urban Flow Inference
inferred← citeshttps://doi.org/10.12677/ojtt.2025.144045openalex-snapshot
Low-Rank Decomposition Method for Spatiotemporal Graph Neural Network-Based Traffic Flow Prediction
inferred← citeshttps://doi.org/10.5753/reic.2026.8438openalex-snapshot
Uma Abordagem de Reinicialização Reativa One-Shot para Previsão de Séries Temporais Financeiras sob Mudança de Conceito
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