Search Results for author:
Found 9 papers, 5 papers with code
Ice-Tide: Implicit Cryo-ET Imaging and Deformation Estimation
We introduce ICE-TIDE, a method for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume.
GLIMPSE: Generalized Local Imaging with MLPs
Deep learning is the current de facto state of the art in tomographic imaging.
Implicit Reconstructions from Deformed Projections for CryoET
Cryo-electron tomography (cryoET) is a technique that captures images of biological samples at different tilts, preserving their native state as much as possible.
FunkNN: Neural Interpolation for Functional Generation
Our answer is FunkNN -- a new convolutional network which learns how to reconstruct continuous images at arbitrary coordinates and can be applied to any image dataset.
Joint Cryo-ET Alignment and Reconstruction with Neural Deformation Fields
We show that our approach enables the recovery of high-frequency details that are destroyed without accounting for deformations.
Differentiable Uncalibrated Imaging
We propose a differentiable imaging framework to address uncertainty in measurement coordinates such as sensor locations and projection angles.
Small Transformers Compute Universal Metric Embeddings
We derive embedding guarantees for feature maps implemented by small neural networks called \emph{probabilistic transformers}.
Manifold Rewiring for Unlabeled Imaging
We illustrate our graph denoising framework on regular synthetic graphs and then apply it to single-particle cryo-EM where the measurements are corrupted by very high levels of noise.
Blind inverse problems with isolated spikes
Assume that an unknown integral operator living in some known subspace is observed indirectly, by evaluating its action on a few Dirac masses at unknown locations.
