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Found 5 papers, 3 papers with code
Capturing dynamical correlations using implicit neural representations
The observation and description of collective excitations in solids is a fundamental issue when seeking to understand the physics of a many-body system.
Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector
As the size of a table increases with detector volume for a fixed resolution, this method scales poorly for future larger detectors.
Heterogeneous reconstruction of deformable atomic models in Cryo-EM
Cryogenic electron microscopy (cryo-EM) provides a unique opportunity to study the structural heterogeneity of biomolecules.
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images
We introduce cryoAI, an ab initio reconstruction algorithm for homogeneous conformations that uses direct gradient-based optimization of particle poses and the electron scattering potential from single-particle cryo-EM data.
Real-time sparse-sampled Ptychographic imaging through deep neural networks
Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample.
