Wang, Yuyang

30 publications

ICLR 2025 Denoising Autoregressive Transformers for Scalable Text-to-Image Generation Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Joshua M. Susskind, Shuangfei Zhai

ICML 2025 INRFlow: Flow Matching for INRs in Ambient Space Yuyang Wang, Anurag Ranjan, Joshua M. Susskind, Miguel Ángel Bautista

NeurIPS 2025 STARFlow: Scaling Latent Normalizing Flows for High-Resolution Image Synthesis Jiatao Gu, Tianrong Chen, David Berthelot, Huangjie Zheng, Yuyang Wang, Ruixiang Zhang, Laurent Dinh, Miguel Ángel Bautista, Joshua M. Susskind, Shuangfei Zhai

ICLR 2024 Manifold Diffusion Fields Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista

ICML 2024 Swallowing the Bitter Pill: Simplified Scalable Conformer Generation Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

ICMLW 2024 Swallowing the Bitter Pill: Simplified Scalable Conformer Generation Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

AISTATS 2023 But Are You Sure? an Uncertainty-Aware Perspective on Explainable AI Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan

AISTATS 2023 Coherent Probabilistic Forecasting of Temporal Hierarchies Syama Sundar Rangapuram, Shubham Kapoor, Rajbir Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider

NeurIPSW 2023 Generating Molecular Conformer Fields Yuyang Wang, Ahmed Elhag, Navdeep Jaitly, Joshua Susskind, Miguel Bautista

NeurIPS 2023 PreDiff: Precipitation Nowcasting with Latent Diffusion Models Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle Maddix, Yi Zhu, Mu Li, Yuyang Wang

NeurIPS 2023 Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang

AISTATS 2022 Learning Quantile Functions Without Quantile Crossing for Distribution-Free Time Series Forecasting Youngsuk Park, Danielle Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang

AISTATS 2022 Robust Probabilistic Time Series Forecasting Taeho Yoon, Youngsuk Park, Ernest K. Ryu, Yuyang Wang

AAAI 2022 Context Uncertainty in Contextual Bandits with Applications to Recommender Systems Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang

ICML 2022 Domain Adaptation for Time Series Forecasting via Attention Sharing Xiaoyong Jin, Youngsuk Park, Danielle Maddix, Hao Wang, Yuyang Wang

NeurIPS 2022 Earthformer: Exploring Space-Time Transformers for Earth System Forecasting Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung

NeurIPS 2022 On the Detrimental Effect of Invariances in the Likelihood for Variational Inference Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus

CoRL 2021 Adversarially Robust Imitation Learning Jianren Wang, Ziwen Zhuang, Yuyang Wang, Hang Zhao

L4DC 2021 Bridging Physics-Based and Data-Driven Modeling for Learning Dynamical Systems Rui Wang, Danielle Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu

ICML 2021 Correcting Exposure Bias for Link Recommendation Shantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang

ICML 2021 Variance Reduced Training with Stratified Sampling for Forecasting Models Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster

MLOSS 2020 GluonTS: Probabilistic and Neural Time Series Modeling in Python 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 2019 Deep Factors for Forecasting Yuyang Wang, Alex Smola, Danielle Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski

ECML-PKDD 2019 FastPoint: Scalable Deep Point Processes Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola

AISTATS 2019 Probabilistic Forecasting with Spline Quantile Function RNNs Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski

NeurIPS 2018 Deep State Space Models for Time Series Forecasting Syama Sundar Rangapuram, Matthias W Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski

ICML 2015 Sparse Variational Inference for Generalized GP Models Rishit Sheth, Yuyang Wang, Roni Khardon

COLT 2012 Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions Yuyang Wang, Roni Khardon, Dmitry Pechyony, Rosie Jones

ECML-PKDD 2012 Sparse Gaussian Processes for Multi-Task Learning Yuyang Wang, Roni Khardon

ECML-PKDD 2010 Shift-Invariant Grouped Multi-Task Learning for Gaussian Processes Yuyang Wang, Roni Khardon, Pavlos Protopapas