Temporal Convolutional Networks


Temporal convolutional networks (TCNs) are deep learning models that use 1D convolutions for sequence modeling tasks.

A Spatiotemporal Radar-Based Precipitation Model for Water Level Prediction and Flood Forecasting

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Mar 25, 2025
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SChanger: Change Detection from a Semantic Change and Spatial Consistency Perspective

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Mar 26, 2025
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Burst Image Super-Resolution with Mamba

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Mar 25, 2025
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Temporal-Spatial Attention Network (TSAN) for DoS Attack Detection in Network Traffic

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Mar 21, 2025
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GazeSCRNN: Event-based Near-eye Gaze Tracking using a Spiking Neural Network

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Mar 20, 2025
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Rolling Forward: Enhancing LightGCN with Causal Graph Convolution for Credit Bond Recommendation

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Mar 18, 2025
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Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition

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Mar 21, 2025
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SCAN-BEST: Efficient Sub-6GHz-Aided Near-field Beam Selection with Formal Reliability Guarantees

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Mar 20, 2025
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DynSTG-Mamba: Dynamic Spatio-Temporal Graph Mamba with Cross-Graph Knowledge Distillation for Gait Disorders Recognition

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Mar 17, 2025
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TGBFormer: Transformer-GraphFormer Blender Network for Video Object Detection

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Mar 18, 2025
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