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Found 3 papers, 2 papers with code
Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification
Stock trend classification remains a fundamental yet challenging task, owing to the intricate time-evolving dynamics between and within stocks.
DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction
Moreover, the ablation study and sensitivity study further illustrate the effectiveness of the proposed method in modeling the time-evolving inter-stock and intra-stock dynamics.
NeLF-Pro: Neural Light Field Probes for Multi-Scale Novel View Synthesis
In contrast to previous fast reconstruction methods that represent the 3D scene globally, we model the light field of a scene as a set of local light field feature probes, parameterized with position and multi-channel 2D feature maps.
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