Search Results for author: Tian Xie

Found 11 papers, 5 papers with code

Crystal Diffusion Variational Autoencoder for Periodic Material Generation

1 code implementation12 Oct 2021 Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi Jaakkola

Generating the periodic structure of stable materials is a long-standing challenge for the material design community.


Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations

no code implementations13 Jan 2021 Tian Xie, Arthur France-Lanord, Yanming Wang, Jeffrey Lopez, Michael Austin Stolberg, Megan Hill, Graham Michael Leverick, Rafael Gomez-Bombarelli, Jeremiah A. Johnson, Yang Shao-Horn, Jeffrey C. Grossman

We demonstrate that a multi-task graph neural network can learn from a large amount of noisy, biased data and a small number of unbiased data and reduce both random and systematic errors in predicting the transport properties of polymer electrolytes.

GraphHop: An Enhanced Label Propagation Method for Node Classification

1 code implementation7 Jan 2021 Tian Xie, Bin Wang, C. -C. Jay Kuo

In Step 2, a new label vector is predicted for each node based on the label of the node itself and the aggregated label information obtained in Step 1.

General Classification Graph Convolutional Network +3

High Dimensional Forecast Combinations Under Latent Structures

no code implementations19 Oct 2020 Zhentao Shi, Liangjun Su, Tian Xie

This paper presents a novel high dimensional forecast combination estimator in the presence of many forecasts and potential latent group structures.


Boosting Retailer Revenue by Generated Optimized Combined Multiple Digital Marketing Campaigns

no code implementations9 Sep 2020 Yafei Xu, Tian Xie, Yu Zhang

Secondly, based on the sub-modular optimization theory and the DMC pool by DMCNet, the generated combined multiple DMCs are ranked with respect to their revenue generation strength then the top three ranked campaigns are returned to the sellers' back-end management system, so that retailers can set combined multiple DMCs for their online shops just in one-shot.

Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs

1 code implementation27 Jun 2019 Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi

Existing techniques either cannot be scaled to large-scale bipartite graphs that have limited labels or cannot exploit the unique structure of bipartite graphs, which have distinct node features in two domains.

Recommendation Systems Representation Learning

Domain Representation for Knowledge Graph Embedding

no code implementations26 Mar 2019 Cunxiang Wang, Feiliang Ren, Zhichao Lin, Chenxv Zhao, Tian Xie, Yue Zhang

Embedding entities and relations into a continuous multi-dimensional vector space have become the dominant method for knowledge graph embedding in representation learning.

Knowledge Graph Embedding Link Prediction

Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials

1 code implementation18 Feb 2019 Tian Xie, Arthur France-Lanord, Yanming Wang, Yang Shao-Horn, Jeffrey C. Grossman

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges.

Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks

no code implementations9 Jul 2018 Tian Xie, Jeffrey C. Grossman

We demonstrate the potential for such a visualization approach by showing that patterns emerge automatically that reflect similarities at different scales in three representative classes of materials: perovskites, elemental boron, and general inorganic crystals, covering material spaces of different compositions, structures, and both.

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Dendrite Suppression with Li Metal Anode

no code implementations12 Apr 2018 Zeeshan Ahmad, Tian Xie, Chinmay Maheshwari, Jeffrey C. Grossman, Venkatasubramanian Viswanathan

We predict over 20 mechanically anisotropic interfaces between Li metal and 6 solid electrolytes which can be used to suppress dendrite growth.

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

3 code implementations Phys. Rev. Lett. 2017 Tian Xie, Jeffrey C. Grossman

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights.

Band Gap Formation Energy Materials Science

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