Yuyang Wang - RankMe

75 papers A* 12A 5Journal 52Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning. CoRR Zelin He, Boran Han, Xiyuan Zhang, Shuai Zhang, Haotian Lin, Qi Zhu, Haoyang Fang, Danielle C. Maddix, Abdul Fatir Ansari, Akash Chandrayan, Abhinav Pradhan, Yuyang Wang, Matthew Reimherr
2025	J	`jnl`	Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach. CoRR Dheeraj Baby, Boran Han, Shuai Zhang, Cuixiong Hu, Yuyang Wang, Yuxiang Wang
2025	J	`jnl`	Chronos-2: From Univariate to Universal Forecasting. CoRR Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken, Andreas Auer, Boran Han, Pedro Mercado, Syama Sundar Rangapuram, Huibin Shen, Lorenzo Stella, Xiyuan Zhang, Mononito Goswami, Shubham Kapoor, Danielle C. Maddix, Pablo Guerron, Tony Hu, Junming Yin, Nick Erickson, Prateek Mutalik Desai, Hao Wang, Huzefa Rangwala, George Karypis, Yuyang Wang, Michael Bohlke-Schneider
2025	J	`jnl`	ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. CoRR Sebastian Pineda-Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Senetaire, Caner Turkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Yuyang Wang, Syama Sundar Rangapuram
2025	J	`jnl`	CrEst: Credibility Estimation for Contexts in LLMs via Weak Supervision. CoRR Dyah Adila, Shuai Zhang, Boran Han, Bonan Min, Yuyang Wang
2025	J	`jnl`	Effectively Steer LLM To Follow Preference via Building Confident Directions. CoRR Bingqing Song, Boran Han, Shuai Zhang, Hao Wang, Haoyang Fang, Bonan Min, Yuyang Wang, Mingyi Hong
2025	J	`jnl`	End-to-End Probabilistic Framework for Learning with Hard Constraints. CoRR Utkarsh Utkarsh, Danielle C. Maddix, Ruijun Ma, Michael W. Mahoney, Yuyang Wang
2025	J	`jnl`	MLZero: A Multi-Agent System for End-to-end Machine Learning Automation. CoRR Haoyang Fang, Boran Han, Nick Erickson, Xiyuan Zhang, Su Zhou, Anirudh Dagar, Jiani Zhang, Ali Caner Türkmen, Cuixiong Hu, Huzefa Rangwala, Ying Nian Wu, Yuyang Wang, George Karypis
2025	J	`jnl`	Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility. CoRR Annan Yu, Danielle C. Maddix, Boran Han, Xiyuan Zhang, Abdul Fatir Ansari, Oleksandr Shchur, Christos Faloutsos, Andrew Gordon Wilson, Michael W. Mahoney, Yuyang Wang
2025	J	`jnl`	Understanding the Implicit Biases of Design Choices for Time Series Foundation Models. CoRR Annan Yu, Danielle C. Maddix, Boran Han, Xiyuan Zhang, Abdul Fatir Ansari, Oleksandr Shchur, Christos Faloutsos, Andrew Gordon Wilson, Michael W. Mahoney, Yuyang Wang
2025	J	`jnl`	Zero-Shot Time Series Forecasting with Covariates via In-Context Learning. CoRR Andreas Auer, Raghul Parthipan, Pedro Mercado, Abdul Fatir Ansari, Lorenzo Stella, Yuyang Wang, Michael Bohlke-Schneider, Syama Sundar Rangapuram
2025	J	`jnl`	fev-bench: A Realistic Benchmark for Time Series Forecasting. CoRR Oleksandr Shchur, Abdul Fatir Ansari, Caner Turkmen, Lorenzo Stella, Nick Erickson, Pablo Guerron, Michael Bohlke-Schneider, Yuyang Wang
2024	J	`jnl`	A Flexible Forecasting Stack. Proc. VLDB Endow. Tim Januschowski, Yuyang Wang, Jan Gasthaus, Syama Sundar Rangapuram, Caner Türkmen, Jasper Zschiegner, Lorenzo Stella, Michael Bohlke-Schneider, Danielle C. Maddix, Konstantinos Benidis, Alexander Alexandrov, Christos Faloutsos, Sebastian Schelter
2024	J	`jnl`	Chronos: Learning the Language of Time Series. CoRR Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang
2024	J	`jnl`	Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics. CoRR Matthias Karlbauer, Danielle C. Maddix, Abdul Fatir Ansari, Boran Han, Gaurav Gupta, Yuyang Wang, Andrew Stuart, Michael W. Mahoney
2024	J	`jnl`	Discovering Bias in Latent Space: An Unsupervised Debiasing Approach. CoRR Dyah Adila, Shuai Zhang, Boran Han, Yuyang Wang
2024	J	`jnl`	Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization. CoRR Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael W. Mahoney, Andrew Gordon Wilson, Youngsuk Park, Syama Sundar Rangapuram, Danielle C. Maddix, Yuyang Wang
2024	J	`jnl`	Hard Constraint Guided Flow Matching for Gradient-Free Generation of PDE Solutions. CoRR Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Yuyang Wang
2024	J	`jnl`	Transferring Knowledge from Large Foundation Models to Small Downstream Models. CoRR Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Yuyang Wang, Andrew Gordon Wilson
2024	J	`jnl`	Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs. CoRR S. Chandra Mouli, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Andrew Stuart, Michael W. Mahoney, Yuyang Wang
2023	J	`jnl`	AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting. CoRR Oleksandr Shchur, Ali Caner Türkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang
2023	A	`conf`	But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI. AISTATS Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan
2023	A	`conf`	Coherent Probabilistic Forecasting of Temporal Hierarchies. AISTATS Syama Sundar Rangapuram, Shubham Kapoor, Rajbir-Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider
2023	J	`jnl`	Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski
2023	J	`jnl`	Deep Non-Parametric Time Series Forecaster. CoRR Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski
2023	A*	`conf`	PreDiff: Precipitation Nowcasting with Latent Diffusion Models. NeurIPS Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
2023	J	`jnl`	PreDiff: Precipitation Nowcasting with Latent Diffusion Models. CoRR Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
2023	A*	`conf`	Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. NeurIPS Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
2023	J	`jnl`	Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. CoRR Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
2023	J	`jnl`	Testing Causality for High Dimensional Data. CoRR Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang
2023	J	`jnl`	Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting. CoRR Hilaf Hasson, Danielle C. Maddix, Yuyang Wang, Gaurav Gupta, Youngsuk Park
2022	A*	`conf`	8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. KDD Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka
2022	A*	`conf`	Context Uncertainty in Contextual Bandits with Applications to Recommender Systems. AAAI Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang
2022	J	`jnl`	Context Uncertainty in Contextual Bandits with Applications to Recommender Systems. CoRR Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang
2022	J	`jnl`	Criteria for Classifying Forecasting Methods. CoRR Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot
2022	A*	`conf`	Domain Adaptation for Time Series Forecasting via Attention Sharing. ICML Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Hao Wang, Yuyang Wang
2022	A*	`conf`	Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. NeurIPS Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
2022	J	`jnl`	Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. CoRR Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
2022	J	`jnl`	First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting. CoRR Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy, Gaurav Gupta, Youngsuk Park, Xingjian Shi, Hao Wang, Danielle C. Maddix, Yuyang Wang
2022	J	`jnl`	Graph-Relational Domain Adaptation. CoRR Zihao Xu, Hao He, Guang-He Lee, Yuyang Wang, Hao Wang
2022	A	`conf`	Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. AISTATS Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang
2022	J	`jnl`	Modeling Advection on Directed Graphs using Matérn Gaussian Processes for Traffic Flow. CoRR Danielle C. Maddix, Nadim Saad, Yuyang Wang
2022	A*	`conf`	On the detrimental effect of invariances in the likelihood for variational inference. NeurIPS Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
2022	J	`jnl`	On the detrimental effect of invariances in the likelihood for variational inference. CoRR Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
2022	A	`conf`	Robust Probabilistic Time Series Forecasting. AISTATS Taeho Yoon, Youngsuk Park, Ernest K. Ryu, Yuyang Wang
2022	J	`jnl`	Robust Probabilistic Time Series Forecasting. CoRR Taeho Yoon, Youngsuk Park, Ernest K. Ryu, Yuyang Wang
2021	J	`jnl`	Attention-based Domain Adaptation for Time Series Forecasting. CoRR Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Yuyang Wang, Xifeng Yan
2021	—	`conf`	Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. L4DC Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu
2021	A*	`conf`	Correcting Exposure Bias for Link Recommendation. ICML Shantanu Gupta, Hao Wang, Zachary C. Lipton, Yuyang Wang
2021	J	`jnl`	Correcting Exposure Bias for Link Recommendation. CoRR Shantanu Gupta, Hao Wang, Zachary C. Lipton, Yuyang Wang
2021	J	`jnl`	Deep Explicit Duration Switching Models for Time Series. CoRR Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski
2021	J	`jnl`	Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR. CoRR Dheeraj Baby, Hilaf Hasson, Yuyang Wang
2021	—	`conf`	GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. ICBINB@NeurIPS Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
2021	J	`jnl`	GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. CoRR Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
2021	J	`jnl`	Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. CoRR Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang
2021	A*	`conf`	Variance Reduced Training with Stratified Sampling for Forecasting Models. ICML Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean P. Foster
2021	J	`jnl`	Variance Reduction in Training Forecasting Models with Subgroup Sampling. CoRR Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean P. Foster
2021	J	`jnl`	Zero-Shot Recommender Systems. CoRR Hao Ding, Yifei Ma, Anoop Deoras, Yuyang Wang, Hao Wang
2020	J	`jnl`	Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. CoRR Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu
2020	—	`conf`	Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola
2020	—	`conf`	Forecasting Big Time Series: Theory and Practice. WWW (Companion Volume) Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2020	J	`jnl`	GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang
2020	J	`jnl`	Intermittent Demand Forecasting with Renewal Processes. CoRR Ali Caner Türkmen, Tim Januschowski, Yuyang Wang, Ali Taylan Cemgil
2019	—	`conf`	Classical and Contemporary Approaches to Big Time Series Forecasting. SIGMOD Conference Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2019	A*	`conf`	Deep Factors for Forecasting. ICML Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski
2019	J	`jnl`	Deep Factors for Forecasting. CoRR Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski
2019	—	`conf`	FastPoint: Scalable Deep Point Processes. ECML/PKDD (2) Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola
2019	A*	`conf`	Forecasting Big Time Series: Theory and Practice. KDD Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2019	J	`jnl`	GluonTS: Probabilistic Time Series Models in Python. CoRR Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang
2019	J	`jnl`	Intermittent Demand Forecasting with Deep Renewal Processes. CoRR Ali Caner Türkmen, Yuyang Wang, Tim Januschowski
2019	A	`conf`	Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski
2018	J	`jnl`	Deep Factors with Gaussian Processes for Forecasting. CoRR Danielle C. Maddix, Yuyang Wang, Alex Smola
2018	A*	`conf`	Deep State Space Models for Time Series Forecasting. NeurIPS Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski
2018	J	`jnl`	Forecasting Big Time Series: Old and New. Proc. VLDB Endow. Christos Faloutsos, Jan Gasthaus, Tim Januschowski, Yuyang Wang
2017	J	`jnl`	Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. CoRR Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert