Search Results for author: Chen Cai

Found 17 papers, 7 papers with code

Generative Coarse-Graining of Molecular Conformations

1 code implementation28 Jan 2022 Wujie Wang, Minkai Xu, Chen Cai, Benjamin Kurt Miller, Tess Smidt, Yusu Wang, Jian Tang, Rafael Gómez-Bombarelli

Coarse-graining (CG) of molecular simulations simplifies the particle representation by grouping selected atoms into pseudo-beads and drastically accelerates simulation.

Convergence of Invariant Graph Networks

no code implementations25 Jan 2022 Chen Cai, Yusu Wang

Building upon this result, we prove the convergence of $k$-IGN under the model of \citet{ruiz2020graphon}, where we access the edge weight but the convergence error is measured for graphon inputs.

Traffic4cast -- Large-scale Traffic Prediction using 3DResNet and Sparse-UNet

1 code implementation10 Nov 2021 Bo wang, Reza Mohajerpoor, Chen Cai, Inhi Kim, Hai L. Vu

The aim is to build a machine learning model for predicting the normalized average traffic speed and flow of the subregions of multiple large-scale cities using historical data points.

Traffic Prediction

Equivariant Subgraph Aggregation Networks

1 code implementation ICLR 2022 Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

Thus, we propose to represent each graph as a set of subgraphs derived by some predefined policy, and to process it using a suitable equivariant architecture.

Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph

no code implementations12 Apr 2021 Chen Cai, Nikolaos Vlassis, Lucas Magee, Ran Ma, Zeyu Xiong, Bahador Bahmani, Teng-Fong Wong, Yusu Wang, WaiChing Sun

Comparisons among predictions inferred from training the CNN and those from graph convolutional neural networks (GNN) with and without the equivariant constraint indicate that the equivariant graph neural network seems to perform better than the CNN and GNN without enforcing equivariant constraints.

Sanity Check for Persistence Diagrams

no code implementations ICLR Workshop GTRL 2021 Chen Cai

To better understand the power and limitation of persistence diagrams, we carry out a range of experiments on both graph and shape data, aiming to decouple and inspect the effects of different factors involved.

Graph Classification Topological Data Analysis

Graph Coarsening with Neural Networks

no code implementations ICLR 2021 Chen Cai, Dingkang Wang, Yusu Wang

As large-scale graphs become increasingly more prevalent, it poses significant computational challenges to process, extract and analyze large graph data.

Energy consumption forecasting using a stacked nonparametric Bayesian approach

no code implementations11 Nov 2020 Dilusha Weeraddana, Nguyen Lu Dang Khoa, Lachlan O Neil, Weihong Wang, Chen Cai

Given these considerations, we construct a stacked GP method where the predictive posteriors of each GP applied to each task are used in the prior and likelihood of the next level GP.

Time Series Time Series Forecasting

A Note on Over-Smoothing for Graph Neural Networks

1 code implementation23 Jun 2020 Chen Cai, Yusu Wang

In this paper, we build upon previous results \cite{oono2019graph} to further analyze the over-smoothing effect in the general graph neural network architecture.

Understanding the Power of Persistence Pairing via Permutation Test

no code implementations16 Jan 2020 Chen Cai, Yusu Wang

For shape segmentation and classification, however, we note that persistence pairing shows significant power on most of the benchmark datasets, and improves over both summaries based on merely critical values, and those based on permutation tests.

General Classification Graph Classification +1

Group Representation Theory for Knowledge Graph Embedding

no code implementations11 Sep 2019 Chen Cai

Knowledge graph embedding has recently become a popular way to model relations and infer missing links.

Knowledge Graph Embedding

Traffic signal control optimization under severe incident conditions using Genetic Algorithm

no code implementations11 Jun 2019 Tuo Mao, Adriana-Simona Mihaita, Chen Cai

Secondly, we apply the optimal signal timings previously found under severe incidents affecting the traffic flow in the network but without any further optimization.

Trip Table Estimation and Prediction for Dynamic Traffic Assignment Applications

no code implementations11 Jun 2019 Sajjad Shafiei, Adriana-Simona Mihaita, Chen Cai

The study focuses on estimating and predicting time-varying origin to destination (OD) trip tables for a dynamic traffic assignment (DTA) model.

Time Series

Network Representation Learning: Consolidation and Renewed Bearing

1 code implementation2 May 2019 Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, Balaraman Ravindran, Srinivasan Parthasarathy

An important area of research that has emerged over the last decade is the use of graphs as a vehicle for non-linear dimensionality reduction in a manner akin to previous efforts based on manifold learning with uses for downstream database processing, machine learning and visualization.

Dimensionality Reduction General Classification +3

A simple yet effective baseline for non-attributed graph classification

2 code implementations8 Nov 2018 Chen Cai, Yusu Wang

We test our baseline representation for the graph classification task on a range of graph datasets.

Classification General Classification +4

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