12 papers
FinMamba: Market-Aware Graph Enhanced Multi-Level Mamba for Stock Movement Prediction
Yifan Hu, Peiyuan Liu, Yuante Li +5
Recently, combining stock features with inter-stock correlations has become a common and effective approach for stock movement prediction. However, financial data presents signific…
Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting
Yixin Wang, Yifan Hu, Peiyuan Liu +3
Time series forecasting remains a challenging problem due to the intricate entanglement of intra-period fluctuations and inter-period trends. While recent advances have attempted t…
FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting
Yifan Hu, Yuante Li, Peiyuan Liu +6
Financial time series (FinTS) record the behavior of human-brain-augmented decision-making, capturing valuable historical information that can be leveraged for profitable investmen…
Analytical Results for Two Exponential Family Distributions in Hierarchical Dirichlet Processes
Naiqi Li
The Hierarchical Dirichlet Process (HDP) provides a flexible Bayesian nonparametric framework for modeling grouped data with a shared yet unbounded collection of mixture components…
ProcGen3D: Learning Neural Procedural Graph Representations for Image-to-3D Reconstruction
Xinyi Zhang, Daoyi Gao, Naiqi Li +1
We introduce ProcGen3D, a new approach for 3D content creation by generating procedural graph abstractions of 3D objects, which can then be decoded into rich, complex 3D assets. In…
Logic-of-Thought: Empowering Large Language Models with Logic Programs for Solving Puzzles in Natural Language
Naiqi Li, Peiyuan Liu, Zheng Liu +3
Solving puzzles in natural language poses a long-standing challenge in AI. While large language models (LLMs) have recently shown impressive capabilities in a variety of tasks, the…