Sara Fridovich-Keil

36 papers A* 10B 1Journal 22Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
3D Field of Junctions: A Noise-Robust, Training-Free Structural Prior for Volumetric Inverse Problems.
CoRR
Namhoon Kim, Narges Moeini, Justin Romberg, Sara Fridovich-Keil
2026 J jnl
Accurate, Provable, and Fast Polychromatic Tomographic Reconstruction: A Variational Inequality Approach.
SIAM J. Imaging Sci.
Mengqi Lou, Kabir Aladin Verchand, Sara Fridovich-Keil, Ashwin Pananjady
2026 J jnl
Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction.
IEEE Trans. Inf. Theory
Sara Fridovich-Keil, Fabrizio Valdivia, Gordon Wetzstein, Benjamin Recht, Mahdi Soltanolkotabi
2026 J jnl
Perfusion Imaging and Single Material Reconstruction in Polychromatic Photon Counting CT.
CoRR
Namhoon Kim, Ashwin Pananjady, Amir Pourmorteza, Sara Fridovich-Keil
2025 J jnl
A Recovery Guarantee for Sparse Neural Networks.
CoRR
Sara Fridovich-Keil, Mert Pilanci
2025 J jnl
Accurate, provable, and fast nonlinear tomographic reconstruction: A variational inequality approach.
CoRR
Mengqi Lou, Kabir Aladin Verchand, Sara Fridovich-Keil, Ashwin Pananjady
2025 A* conf
Geometric Algebra Planes: Convex Implicit Neural Volumes.
ICML
Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein, Mert Pilanci
2025 J jnl
Grids Often Outperform Implicit Neural Representations.
CoRR
Namhoon Kim, Sara Fridovich-Keil
2025 J jnl
Patch-Based Diffusion for Data-Efficient, Radiologist-Preferred MRI Reconstruction.
CoRR
Rohan Sanda, Asad Aali, Andrew Johnston, Eduardo Reis, Jonathan Singh, Gordon Wetzstein, Sara Fridovich-Keil
2025 — conf
Towards Distribution-Shift Uncertainty Estimation for Inverse Problems with Generative Priors.
CAMSAP
Namhoon Kim, Sara Fridovich-Keil
2025 J jnl
Towards Distribution-Shift Uncertainty Estimation for Inverse Problems with Generative Priors.
CoRR
Namhoon Kim, Sara Fridovich-Keil
2024 J jnl
Geometric Algebra Planes: Convex Implicit Neural Volumes.
CoRR
Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein, Mert Pilanci
2024 J jnl
Solving Inverse Problems in Protein Space Using Diffusion-Based Priors.
CoRR
Axel Levy, Eric R. Chan, Sara Fridovich-Keil, Frédéric Poitevin, Ellen D. Zhong, Gordon Wetzstein
2024 B conf
ThermalNeRF: Thermal Radiance Fields.
ICCP
Yvette Y. Lin, Xin-Yi Pan, Sara Fridovich-Keil, Gordon Wetzstein
2024 J jnl
ThermalNeRF: Thermal Radiance Fields.
CoRR
Yvette Y. Lin, Xin-Yi Pan, Sara Fridovich-Keil, Gordon Wetzstein
2023 J jnl
Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction.
CoRR
Sara Fridovich-Keil, Fabrizio Valdivia, Gordon Wetzstein, Benjamin Recht, Mahdi Soltanolkotabi
2023 A* conf
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance.
CVPR
Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbæk Warburg, Benjamin Recht, Angjoo Kanazawa
2023 J jnl
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance.
CoRR
Sara Fridovich-Keil, Giacomo Meanti, Frederik Warburg, Benjamin Recht, Angjoo Kanazawa
2023 A* conf
Neural Microfacet Fields for Inverse Rendering.
ICCV
Alexander Mai, Dor Verbin, Falko Kuester, Sara Fridovich-Keil
2023 J jnl
Neural Microfacet Fields for Inverse Rendering.
CoRR
Alexander Mai, Dor Verbin, Falko Kuester, Sara Fridovich-Keil
2023 — —
Photorealistic Reconstruction from First Principles
Sara Fridovich-Keil
2023 J jnl
Volumetric Reconstruction Resolves Off-Resonance Artifacts in Static and Dynamic PROPELLER MRI.
CoRR
Annesha Ghosh, Gordon Wetzstein, Mert Pilanci, Sara Fridovich-Keil
2022 A* conf
Models Out of Line: A Fourier Lens on Distribution Shift Robustness.
NeurIPS
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer
2022 J jnl
Models Out of Line: A Fourier Lens on Distribution Shift Robustness.
CoRR
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Peer-Timo Bremer
2022 A* conf
Plenoxels: Radiance Fields without Neural Networks.
CVPR
Sara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa
2022 A* conf
Spectral Bias in Practice: The Role of Function Frequency in Generalization.
NeurIPS
Sara Fridovich-Keil, Raphael Gontijo Lopes, Rebecca Roelofs
2022 A* conf
When does dough become a bagel? Analyzing the remaining mistakes on ImageNet.
NeurIPS
Vijay Vasudevan, Benjamin Caine, Raphael Gontijo Lopes, Sara Fridovich-Keil, Rebecca Roelofs
2022 J jnl
When does dough become a bagel? Analyzing the remaining mistakes on ImageNet.
CoRR
Vijay Vasudevan, Benjamin Caine, Raphael Gontijo Lopes, Sara Fridovich-Keil, Rebecca Roelofs
2021 J jnl
Plenoxels: Radiance Fields without Neural Networks.
CoRR
Alex Yu, Sara Fridovich-Keil, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa
2021 J jnl
Spectral Bias in Practice: The Role of Function Frequency in Generalization.
CoRR
Sara Fridovich-Keil, Raphael Gontijo Lopes, Rebecca Roelofs
2020 A* conf
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.
NeurIPS
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, Ren Ng
2020 J jnl
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.
CoRR
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, Ren Ng
2020 A* conf
Neural Kernels Without Tangents.
ICML
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht
2020 J jnl
Neural Kernels Without Tangents.
CoRR
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Ludwig Schmidt, Jonathan Ragan-Kelley, Benjamin Recht
2019 A* conf
A Meta-Analysis of Overfitting in Machine Learning.
NeurIPS
Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht, Sara Fridovich-Keil, Moritz Hardt, John Miller, Ludwig Schmidt
2018 — conf
Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos.
GlobalSIP
Sara Fridovich-Keil, Peter J. Ramadge