Hayden Schaeffer

62 papers Misc 1Journal 55Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adam Improves Muon: Adaptive Moment Estimation with Orthogonalized Momentum. CoRR Minxin Zhang, Yuxuan Liu, Hayden Schaeffer
2026	J	`jnl`	DeepONet as a multi-Operator extrapolation model: Distributed pretraining with physics-Informed fine-Tuning. J. Comput. Phys. Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2026	J	`jnl`	VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction. Trans. Mach. Learn. Res. Yadi Cao, Yuxuan Liu, Liu Yang, Rose Yu, Hayden Schaeffer, Stanley J. Osher
2025	J	`jnl`	A Deep Learning Framework for Multi-Operator Learning: Architectures and Approximation Theory. CoRR Adrien Weihs, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer
2025	J	`jnl`	A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions. CoRR Elisa Negrini, Yuxuan Liu, Liu Yang, Stanley J. Osher, Hayden Schaeffer
2025	J	`jnl`	A discretization-invariant extension and analysis of some deep operator networks. J. Comput. Appl. Math. Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
2025	J	`jnl`	AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates. CoRR Minxin Zhang, Yuxuan Liu, Hayden Schaeffer
2025	J	`jnl`	BCAT: A Block Causal Transformer for PDE Foundation Models for Fluid Dynamics. CoRR Yuxuan Liu, Jingmin Sun, Hayden Schaeffer
2025	J	`jnl`	Cauchy Random Features for Operator Learning in Sobolev Space. CoRR Chunyang Liao, Deanna Needell, Hayden Schaeffer
2025	J	`jnl`	Finite Element Representation Network (FERN) for Operator Learning with a Localized Trainable Basis. CoRR Zecheng Zhang, Hao Liu, Guosheng Fu, Hayden Schaeffer, Guang Lin
2025	J	`jnl`	PI-MFM: Physics-informed multimodal foundation model for solving partial differential equations. CoRR Min Zhu, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer, Lu Lu
2025	J	`jnl`	Regularized Random Fourier Features and Finite Element Reconstruction for Operator Learning in Sobolev Space. CoRR Xinyue Yu, Hayden Schaeffer
2024	J	`jnl`	Bayesian Deep Operator Learning for Homogenized to Fine-Scale Maps for Multiscale PDE. Multiscale Model. Simul. Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	LeMON: Learning to Learn Multi-Operator Networks. CoRR Jingmin Sun, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study. CoRR Hao Liu, Zecheng Zhang, Wenjing Liao, Hayden Schaeffer
2024	J	`jnl`	PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics. CoRR Yuxuan Liu, Jingmin Sun, Xinjie He, Griffin Pinney, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	PROSE: Predicting Multiple Operators and Symbolic Expressions using multimodal transformers. Neural Networks Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation Model. CoRR Derek Jollie, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation. CoRR Jingmin Sun, Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction. CoRR Yadi Cao, Yuxuan Liu, Liu Yang, Rose Yu, Hayden Schaeffer, Stanley J. Osher
2023	J	`jnl`	A discretization-invariant extension and analysis of some deep operator networks. CoRR Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
2023	J	`jnl`	Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE. CoRR Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	PROSE: Predicting Operators and Symbolic Expressions using Multimodal Transformers. CoRR Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
2022	J	`jnl`	BelNet: Basis enhanced learning, a mesh-free neural operator. CoRR Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
2022	—	`conf`	Concentration of Random Feature Matrices in High-Dimensions. MSML Zhijun Chen, Hayden Schaeffer, Rachel A. Ward
2022	J	`jnl`	Concentration of Random Feature Matrices in High-Dimensions. CoRR Zhijun Chen, Hayden Schaeffer, Rachel A. Ward
2022	J	`jnl`	HARFE: Hard-Ridge Random Feature Expansion. CoRR Esha Saha, Hayden Schaeffer, Giang Tran
2022	J	`jnl`	Random Feature Models for Learning Interacting Dynamical Systems. CoRR Yuxuan Liu, Scott G. McCalla, Hayden Schaeffer
2022	—	`conf`	SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning. MSML Yuege Xie, Robert Shi, Hayden Schaeffer, Rachel A. Ward
2022	J	`jnl`	SRMD: Sparse Random Mode Decomposition. CoRR Nicholas Richardson, Hayden Schaeffer, Giang Tran
2021	J	`jnl`	Conditioning of Random Feature Matrices: Double Descent and Generalization Error. CoRR Zhijun Chen, Hayden Schaeffer
2021	J	`jnl`	Function Approximation via Sparse Random Features. CoRR Abolfazl Hashemi, Hayden Schaeffer, Robert Shi, Ufuk Topcu, Giang Tran, Rachel A. Ward
2021	—	`conf`	Reduced Order Modeling using Shallow ReLU Networks with Grassmann Layers. MSML Kayla Bollinger, Hayden Schaeffer
2021	J	`jnl`	SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning. CoRR Yuege Xie, Bobby Shi, Hayden Schaeffer, Rachel A. Ward
2020	J	`jnl`	Extending the Step-Size Restriction for Gradient Descent to Avoid Strict Saddle Points. SIAM J. Math. Data Sci. Hayden Schaeffer, Scott G. McCalla
2020	J	`jnl`	Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples. Multiscale Model. Simul. Hayden Schaeffer, Giang Tran, Rachel A. Ward, Linan Zhang
2020	J	`jnl`	Forward Stability of ResNet and Its Variants. J. Math. Imaging Vis. Linan Zhang, Hayden Schaeffer
2020	—	`conf`	NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data. MSML Yifan Sun, Linan Zhang, Hayden Schaeffer
2020	J	`jnl`	Recovery guarantees for polynomial coefficients from weakly dependent data with outliers. J. Approx. Theory Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel A. Ward
2020	J	`jnl`	Reduced Order Modeling using Shallow ReLU Networks with Grassmann Layers. CoRR Kayla Bollinger, Hayden Schaeffer
2019	J	`jnl`	Extending the step-size restriction for gradient descent to avoid strict saddle points. CoRR Hayden Schaeffer, Scott G. McCalla
2019	J	`jnl`	NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data. CoRR Yifan Sun, Linan Zhang, Hayden Schaeffer
2019	J	`jnl`	On the Convergence of the SINDy Algorithm. Multiscale Model. Simul. Linan Zhang, Hayden Schaeffer
2018	J	`jnl`	Extracting Sparse High-Dimensional Dynamics from Limited Data. SIAM J. Appl. Math. Hayden Schaeffer, Giang Tran, Rachel A. Ward
2018	J	`jnl`	Extracting structured dynamical systems using sparse optimization with very few samples. CoRR Hayden Schaeffer, Giang Tran, Rachel A. Ward, Linan Zhang
2018	J	`jnl`	Forward Stability of ResNet and Its Variants. CoRR Linan Zhang, Hayden Schaeffer
2018	J	`jnl`	On the Convergence of the SINDy Algorithm. CoRR Linan Zhang, Hayden Schaeffer
2018	J	`jnl`	Recovery guarantees for polynomial approximation from dependent data with outliers. CoRR Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel A. Ward
2016	J	`jnl`	An Accelerated Method for Nonlinear Elliptic PDE. J. Sci. Comput. Hayden Schaeffer, Thomas Y. Hou
2015	J	`jnl`	An L SIAM J. Appl. Math. Giang Tran, Hayden Schaeffer, William M. Feldman, Stanley J. Osher
2015	J	`jnl`	Real-Time Adaptive Video Compression. SIAM J. Sci. Comput. Hayden Schaeffer, Yi Yang, Hongkai Zhao, Stanley J. Osher
2015	J	`jnl`	Space-Time Regularization for Video Decompression. SIAM J. Imaging Sci. Hayden Schaeffer, Yi Yang, Stanley J. Osher
2015	J	`jnl`	Sparse + low-energy decomposition for viscous conservation laws. J. Comput. Phys. Thomas Y. Hou, Qin Li, Hayden Schaeffer
2014	J	`jnl`	Active Contours with Free Endpoints. J. Math. Imaging Vis. Hayden Schaeffer, Luminita A. Vese
2014	J	`jnl`	On the Compressive Spectral Method. Multiscale Model. Simul. Alan Mackey, Hayden Schaeffer, Stanley J. Osher
2014	J	`jnl`	Variational Dynamics of Free Triple Junctions. J. Sci. Comput. Hayden Schaeffer, Luminita A. Vese
2013	J	`jnl`	A Low Patch-Rank Interpretation of Texture. SIAM J. Imaging Sci. Hayden Schaeffer, Stanley J. Osher
2013	—	`conf`	Boundary detection in echocardiography using a Split Bregman edge detector and a topology preserving level set approach. ISBI Nóirín Duggan, Hayden Schaeffer, Carole Le Guyader, Edward Jones, Martin Glavin, Luminita A. Vese
2013	Misc	`conf`	Mixing space-time derivatives for video compressive sensing. ACSSC Yi Yang, Hayden Schaeffer, Wotao Yin, Stanley J. Osher
2013	—	`—`	Variational Models for Fine Structures. Hayden Schaeffer