Search Results for author: Yao Xuan

Found 8 papers, 2 papers with code

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting

2 code implementations NeurIPS 2019 Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen, Yu-Xiang Wang, Xifeng Yan

Time series forecasting is an important problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation.

Ranked #27 on Image Generation on ImageNet 64x64 (Bits per dim metric)

Time Series Time Series Forecasting

Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm

no code implementations12 Dec 2020 Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Hector D. Ceniceros

Game theory has been an effective tool in the control of disease spread and in suggesting optimal policies at both individual and area levels.

Sphere2Vec: Self-Supervised Location Representation Learning on Spherical Surfaces

no code implementations29 Sep 2021 Gengchen Mai, Yao Xuan, Wenyun Zuo, Yutong He, Stefano Ermon, Jiaming Song, Krzysztof Janowicz, Ni Lao

Location encoding is valuable for a multitude of tasks where both the absolute positions and local contexts (image, text, and other types of metadata) of spatial objects are needed for accurate predictions.

Image Classification Representation Learning +1

Sphere2Vec: Multi-Scale Representation Learning over a Spherical Surface for Geospatial Predictions

no code implementations25 Jan 2022 Gengchen Mai, Yao Xuan, Wenyun Zuo, Krzysztof Janowicz, Ni Lao

However, a map projection distortion problem rises when applying location encoding models to large-scale real-world GPS coordinate datasets (e. g., species images taken all over the world) - all current location encoding models are designed for encoding points in a 2D (Euclidean) space but not on a spherical surface, e. g., earth surface.

Image Classification Representation Learning

Pandemic Control, Game Theory and Machine Learning

no code implementations18 Aug 2022 Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Hector D. Ceniceros

Game theory has been an effective tool in the control of disease spread and in suggesting optimal policies at both individual and area levels.

Decision Making

Towards General-Purpose Representation Learning of Polygonal Geometries

1 code implementation29 Sep 2022 Gengchen Mai, Chiyu Jiang, Weiwei Sun, Rui Zhu, Yao Xuan, Ling Cai, Krzysztof Janowicz, Stefano Ermon, Ni Lao

For the spatial domain approach, we propose ResNet1D, a 1D CNN-based polygon encoder, which uses circular padding to achieve loop origin invariance on simple polygons.

Representation Learning

Machine Learning and Polymer Self-Consistent Field Theory in Two Spatial Dimensions

no code implementations16 Dec 2022 Yao Xuan, Kris T. Delaney, Hector D. Ceniceros, Glenn H. Fredrickson

A computational framework that leverages data from self-consistent field theory simulations with deep learning to accelerate the exploration of parameter space for block copolymers is presented.

Generative Adversarial Network

Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions

no code implementations30 Jun 2023 Gengchen Mai, Yao Xuan, Wenyun Zuo, Yutong He, Jiaming Song, Stefano Ermon, Krzysztof Janowicz, Ni Lao

So when applied to large-scale real-world GPS coordinate datasets, which require distance metric learning on the spherical surface, both types of models can fail due to the map projection distortion problem (2D) and the spherical-to-Euclidean distance approximation error (3D).

Image Classification Metric Learning +2

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