Hayden Schaeffer

Orcid: 0000-0003-1379-1238

According to our database1, Hayden Schaeffer authored at least 34 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators.
CoRR, 2023

PROSE: Predicting Operators and Symbolic Expressions using Multimodal Transformers.
CoRR, 2023

Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE.
CoRR, 2023

A discretization-invariant extension and analysis of some deep operator networks.
CoRR, 2023

2022
BelNet: Basis enhanced learning, a mesh-free neural operator.
CoRR, 2022

Random Feature Models for Learning Interacting Dynamical Systems.
CoRR, 2022

SRMD: Sparse Random Mode Decomposition.
CoRR, 2022

HARFE: Hard-Ridge Random Feature Expansion.
CoRR, 2022

SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning.
Proceedings of the Mathematical and Scientific Machine Learning, 2022

Concentration of Random Feature Matrices in High-Dimensions.
Proceedings of the Mathematical and Scientific Machine Learning, 2022

2021
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning.
CoRR, 2021

Conditioning of Random Feature Matrices: Double Descent and Generalization Error.
CoRR, 2021

Function Approximation via Sparse Random Features.
CoRR, 2021

Reduced Order Modeling using Shallow ReLU Networks with Grassmann Layers.
Proceedings of the Mathematical and Scientific Machine Learning, 2021

2020
Extending the Step-Size Restriction for Gradient Descent to Avoid Strict Saddle Points.
SIAM J. Math. Data Sci., 2020

Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples.
Multiscale Model. Simul., 2020

Forward Stability of ResNet and Its Variants.
J. Math. Imaging Vis., 2020

Recovery guarantees for polynomial coefficients from weakly dependent data with outliers.
J. Approx. Theory, 2020

NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data.
Proceedings of Mathematical and Scientific Machine Learning, 2020

2019
On the Convergence of the SINDy Algorithm.
Multiscale Model. Simul., 2019

2018
Extracting Sparse High-Dimensional Dynamics from Limited Data.
SIAM J. Appl. Math., 2018

Recovery guarantees for polynomial approximation from dependent data with outliers.
CoRR, 2018

2016
An Accelerated Method for Nonlinear Elliptic PDE.
J. Sci. Comput., 2016

2015
Real-Time Adaptive Video Compression.
SIAM J. Sci. Comput., 2015

Space-Time Regularization for Video Decompression.
SIAM J. Imaging Sci., 2015

An L<sup>1</sup> Penalty Method for General Obstacle Problems.
SIAM J. Appl. Math., 2015

Sparse + low-energy decomposition for viscous conservation laws.
J. Comput. Phys., 2015

2014
On the Compressive Spectral Method.
Multiscale Model. Simul., 2014

Variational Dynamics of Free Triple Junctions.
J. Sci. Comput., 2014

Active Contours with Free Endpoints.
J. Math. Imaging Vis., 2014

2013
Variational Models for Fine Structures.
PhD thesis, 2013

A Low Patch-Rank Interpretation of Texture.
SIAM J. Imaging Sci., 2013

Boundary detection in echocardiography using a Split Bregman edge detector and a topology preserving level set approach.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Mixing space-time derivatives for video compressive sensing.
Proceedings of the 2013 Asilomar Conference on Signals, 2013


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