Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Yuyang Wang

GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics

Dec 18, 2021
Ke Alexander Wang, Danielle Maddix, Yuyang Wang

* NeurIPS 2021 Workshop ICBINB Spotlight 

  Access Paper or Ask Questions

Modeling Advection on Directed Graphs using Matérn Gaussian Processes for Traffic Flow

Dec 14, 2021
Danielle C Maddix, Nadim Saad, Yuyang Wang

* Accepted at the Machine Learning and Physical Sciences NeurIPS 2021 Workshop 

  Access Paper or Ask Questions

AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning

Dec 01, 2021
Rishikesh Magar, Yuyang Wang, Cooper Lorsung, Chen Liang, Hariharan Ramasubramanian, Peiyuan Li, Amir Barati Farimani

* Preprint under review 4 figures, 3 tables 

  Access Paper or Ask Questions

Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR

Nov 22, 2021
Dheeraj Baby, Hilaf Hasson, Yuyang Wang

  Access Paper or Ask Questions

Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting

Nov 12, 2021
Youngsuk Park, Danielle Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang

* 24 pages 

  Access Paper or Ask Questions

Deep Explicit Duration Switching Models for Time Series

Oct 26, 2021
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Turkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski

* Accepted at NeurIPS 2021 

  Access Paper or Ask Questions

A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification

Jul 03, 2021
Chao-Han Huck Yang, Hu Hu, Sabato Marco Siniscalchi, Qing Wang, Yuyang Wang, Xianjun Xia, Yuanjun Zhao, Yuzhong Wu, Yannan Wang, Jun Du, Chin-Hui Lee

* Detection and Classification of Acoustic Scenes and Events (DCASE), 2021 
* 5 figures. DCASE 2021. The project started in November 2020 

  Access Paper or Ask Questions

Correcting Exposure Bias for Link Recommendation

Jun 13, 2021
Shantanu Gupta, Hao Wang, Zachary C. Lipton, Yuyang Wang

  Access Paper or Ask Questions

5G MIMO Data for Machine Learning: Application to Beam-Selection using Deep Learning

Jun 09, 2021
Aldebaro Klautau, Pedro Batista, Nuria Gonzalez-Prelcic, Yuyang Wang, Robert W. Heath Jr

  Access Paper or Ask Questions

Zero-Shot Recommender Systems

May 18, 2021
Hao Ding, Yifei Ma, Anoop Deoras, Yuyang Wang, Hao Wang

  Access Paper or Ask Questions

Variance Reduction in Training Forecasting Models with Subgroup Sampling

Mar 02, 2021
Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster

  Access Paper or Ask Questions

Deep Learning-based Compressive Beam Alignment in mmWave Vehicular Systems

Feb 27, 2021
Yuyang Wang, Nitin Jonathan Myers, Nuria González-Prelcic, Robert W. Heath Jr

* Submitted to the IEEE Transactions on Wireless Communications. Copyright may be transferred without notice, after which this version may no longer be accessible 

  Access Paper or Ask Questions

MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks

Feb 19, 2021
Yuyang Wang, Jianren Wang, Zhonglin Cao, Amir Barati Farimani

  Access Paper or Ask Questions

Attention-based Domain Adaptation for Time Series Forecasting

Feb 17, 2021
Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Yuyang Wang, Xifeng Yan

* 15 pages, 9 figures 

  Access Paper or Ask Questions

Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination

Feb 09, 2021
Yuyang Wang, Zhonglin Cao, Amir Barati Farimani

* Yuyang Wang and Zhonglin Cao contributed equally to this work 

  Access Paper or Ask Questions

Airfoil GAN: Encoding and Synthesizing Airfoils forAerodynamic-aware Shape Optimization

Jan 12, 2021
Yuyang Wang, Kenji Shimada, Amir Barati Farimani

  Access Paper or Ask Questions

Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems

Nov 20, 2020
Rui Wang, Danielle Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu

  Access Paper or Ask Questions

Intermittent Demand Forecasting with Renewal Processes

Oct 04, 2020
Ali Caner Turkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil

  Access Paper or Ask Questions

Intermittent Demand Forecasting with Deep Renewal Processes

Nov 23, 2019
Ali Caner Turkmen, Yuyang Wang, Tim Januschowski

* NeurIPS 2019 Workshop on Temporal Point Processes 

  Access Paper or Ask Questions

GluonTS: Probabilistic Time Series Models in Python

Jun 14, 2019
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang

* ICML Time Series Workshop 2019 

  Access Paper or Ask Questions

Deep Factors for Forecasting

May 28, 2019
Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski

* Proceedings of Machine Learning Research, Volume 97: International Conference on Machine Learning, 2019 
* arXiv admin note: substantial text overlap with arXiv:1812.00098 

  Access Paper or Ask Questions

Deep Factors with Gaussian Processes for Forecasting

Nov 30, 2018
Danielle C. Maddix, Yuyang Wang, Alex Smola

* Third workshop on Bayesian Deep Learning (NeurIPS 2018), Montreal, Canada 

  Access Paper or Ask Questions

Gini-regularized Optimal Transport with an Application to Spatio-Temporal Forecasting

Dec 07, 2017
Lucas Roberts, Leo Razoumov, Lin Su, Yuyang Wang

* 10 pages 

  Access Paper or Ask Questions

Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale

Sep 22, 2017
Matthias Seeger, Syama Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert

  Access Paper or Ask Questions

Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes

May 20, 2013
Yuyang Wang, Roni Khardon, Pavlos Protopapas

* This is an extended version of our ECML 2010 paper entitled "Shift-invariant Grouped Multi-task Learning for Gaussian Processes"; ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III 

  Access Paper or Ask Questions

Online Learning with Pairwise Loss Functions

Jan 22, 2013
Yuyang Wang, Roni Khardon, Dmitry Pechyony, Rosie Jones

* This is an extension of our COLT paper 

  Access Paper or Ask Questions

Nonparametric Bayesian Mixed-effect Model: a Sparse Gaussian Process Approach

Nov 28, 2012
Yuyang Wang, Roni Khardon

* Preliminary version appeared in ECML2012 

  Access Paper or Ask Questions

Nonparametric Bayesian Estimation of Periodic Functions

Mar 07, 2012
Yuyang Wang, Roni Khardon, Pavlos Protopapas

  Access Paper or Ask Questions