Yuyang (Bernie) Wang

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Tim JanuschowskiDatabricks (prior: Zalando, AWS/Amazon, TU Berlin, University College Cork, Zuse Institute Berlin)Email yang diverifikasi di databricks.com
Jan GasthausAWS AI Labs, Amazon Web ServicesEmail yang diverifikasi di ucl.ac.uk
Danielle MaddixAWS AI | Stanford UniversityEmail yang diverifikasi di stanford.edu
Alex SmolaBoson AIEmail yang diverifikasi di smola.org
Abdul Fatir AnsariMachine Learning Scientist at AmazonEmail yang diverifikasi di amazon.com
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinEmail yang diverifikasi di amazon.de
Roni KhardonProfessor of Computer Science, Indiana University, BloomingtonEmail yang diverifikasi di iu.edu
Christos FaloutsosCMUEmail yang diverifikasi di cs.cmu.edu
Michael MahoneyProfessor of Statistics, UC BerkeleyEmail yang diverifikasi di stat.berkeley.edu
Hao WangAssistant Professor of Computer Science, Rutgers UniversityEmail yang diverifikasi di mit.edu
Boran HanAWSEmail yang diverifikasi di g.harvard.edu
Xingjian ShiBoson AIEmail yang diverifikasi di connect.ust.hk
Andrew Gordon WilsonNew York UniversityEmail yang diverifikasi di cims.nyu.edu
Alan EdelmanProfessor of Applied Mathematics, Member Computer Science AI LABS, MITEmail yang diverifikasi di mit.edu
Kari TorkkolaSenior Principal Research Scientist, Amazon.comEmail yang diverifikasi di amazon.com
Dean FosterAmazon, NYCEmail yang diverifikasi di amazon.com
Rose YuAssociate Professor, University of California, San DiegoEmail yang diverifikasi di ucsd.edu
Edo Libertypinecone.ioEmail yang diverifikasi di edoliberty.com
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeEmail yang diverifikasi di cmu.edu

Ikuti

Yuyang (Bernie) Wang

Principal Scientist, AWS AI

Email yang diverifikasi di mit.edu - Beranda

Machine Learning Random Matrix Theory Time Series Forecasting


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Deep state space models for time series forecasting SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ... Advances in neural information processing systems 31, 2018	912	2018
Gluonts: Probabilistic and neural time series modeling in python A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ... Journal of Machine Learning Research 21 (116), 1-6, 2020	404*	2020
Deep learning for time series forecasting: Tutorial and literature survey K Benidis, SS Rangapuram, V Flunkert, Y Wang, D Maddix, C Turkmen, ... ACM Computing Surveys 55 (6), 1-36, 2022	372*	2022
Criteria for classifying forecasting methods T Januschowski, J Gasthaus, Y Wang, D Salinas, V Flunkert, ... International Journal of Forecasting 36 (1), 167-177, 2020	255	2020
Deep Factors for Forecasting Y Wang, A Smola, DC Maddix, J Gasthaus, D Foster, T Januschowski ICML 2019, arXiv preprint arXiv:1905.12417, 2019	238	2019
Chronos: Learning the language of time series AF Ansari, L Stella, C Turkmen, X Zhang, P Mercado, H Shen, O Shchur, ... TMLR arXiv preprint arXiv:2403.07815, 2024	237	2024
Probabilistic forecasting with spline quantile function RNNs J Gasthaus, K Benidis, Y Wang, SS Rangapuram, D Salinas, V Flunkert, ... The 22nd international conference on artificial intelligence and statistics …, 2019	204	2019
Probabilistic Demand Forecasting at Scale YW Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski ... Proceedings of the VLDB Endowment 10 (12), 1694-1705, 2017	186*	2017
Earthformer: Exploring space-time transformers for earth system forecasting Z Gao, X Shi, H Wang, Y Zhu, YB Wang, M Li, DY Yeung Advances in Neural Information Processing Systems 35, 25390-25403, 2022	179	2022
Elastic Machine Learning Algorithms in Amazon SageMaker E Liberty, Z Karnin, B Xiang, L Rouesnel, B Coskun, R Nallapati, ... SIGMOD, 2020	146	2020
Forecasting with trees T Januschowski, Y Wang, K Torkkola, T Erkkilä, H Hasson, J Gasthaus International Journal of Forecasting 38 (4), 1473-1481, 2022	112	2022
Zero-shot recommender systems H Ding, Y Ma, A Deoras, Y Wang, H Wang arXiv preprint arXiv:2105.08318, 2021	97	2021
Domain adaptation for time series forecasting via attention sharing X Jin, Y Park, D Maddix, H Wang, Y Wang International Conference on Machine Learning, 10280-10297, 2022	95	2022
Forecasting big time series: old and new C Faloutsos, J Gasthaus, T Januschowski, Y Wang Proceedings of the VLDB Endowment 11 (12), 2102-2105, 2018	88	2018
Random Matrix Theory and Its Innovative Applications A Edelman, Y Wang Advances in Applied Mathematics, Modeling, and Computational Science, 91-116, 2012	80	2012
Bridging physics-based and data-driven modeling for learning dynamical systems R Wang, D Maddix, C Faloutsos, Y Wang, R Yu Learning for dynamics and control, 385-398, 2021	68	2021
Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions Y Wang, R Khardon, D Pechyony, R Jones Annual Conference on Learning Theory, 2012	67	2012
Prediff: Precipitation nowcasting with latent diffusion models Z Gao, X Shi, B Han, H Wang, X Jin, D Maddix, Y Zhu, M Li, YB Wang Advances in Neural Information Processing Systems 36, 2023	62	2023
Predict, refine, synthesize: Self-guiding diffusion models for probabilistic time series forecasting M Kollovieh, AF Ansari, M Bohlke-Schneider, J Zschiegner, H Wang, ... Advances in Neural Information Processing Systems 36, 2023	54	2023
Deep factors with gaussian processes for forecasting DC Maddix, Y Wang, A Smola NeurIPS Workshop on Bayesian Deep Learning, 2018	54	2018

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