Search Results for author: Baichuan Yuan

Found 5 papers, 0 papers with code

Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data

no code implementations2 Apr 2018 Bao Wang, Xiyang Luo, Fangbo Zhang, Baichuan Yuan, Andrea L. Bertozzi, P. Jeffrey Brantingham

We present a generic framework for spatio-temporal (ST) data modeling, analysis, and forecasting, with a special focus on data that is sparse in both space and time.

Multivariate Spatiotemporal Hawkes Processes and Network Reconstruction

no code implementations15 Nov 2018 Baichuan Yuan, Hao Li, Andrea L. Bertozzi, P. Jeffrey Brantingham, Mason A. Porter

There is often latent network structure in spatial and temporal data and the tools of network analysis can yield fascinating insights into such data.

Variational Autoencoders for Highly Multivariate Spatial Point Processes Intensities

no code implementations ICLR 2020 Baichuan Yuan, Xiaowei Wang, Jianxin Ma, Chang Zhou, Andrea L. Bertozzi, Hongxia Yang

To bridge this gap, we introduce a declustering based hidden variable model that leads to an efficient inference procedure via a variational autoencoder (VAE).

Collaborative Filtering Point Processes +1

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits

no code implementations ICLR 2022 Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan

We show that incorporating frequency information of tokens in the embedding learning problems leads to provably efficient algorithms, and demonstrate that common adaptive algorithms implicitly exploit the frequency information to a large extent.

Language Modelling Recommendation Systems

Do We Really Need Complicated Model Architectures For Temporal Networks?

no code implementations22 Feb 2023 Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi

Recurrent neural network (RNN) and self-attention mechanism (SAM) are the de facto methods to extract spatial-temporal information for temporal graph learning.

Graph Learning Link Prediction

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