Search Results for author:
Found 6 papers, 3 papers with code
RiNALMo: General-Purpose RNA Language Models Can Generalize Well on Structure Prediction Tasks
RiNALMo is the largest RNA language model to date with $650$ million parameters pre-trained on $36$ million non-coding RNA sequences from several available databases.
Estimating Uncertainty in PET Image Reconstruction via Deep Posterior Sampling
The method is based on training a conditional generative adversarial network whose generator approximates sampling from the posterior in Bayesian inversion.
Deep Variational Inverse Scattering
Inverse medium scattering solvers generally reconstruct a single solution without an associated measure of uncertainty.
Implicit Neural Representation for Mesh-Free Inverse Obstacle Scattering
In this paper, we introduce an implicit neural representation-based framework for solving the inverse obstacle scattering problem in a mesh-free fashion.
Single-Pixel Compressive Imaging in Shift-Invariant Spaces via Exact Wavelet Frames
The SI models of the acquisition and the underlying signal lead to an exact discretization of an inherently continuous-domain inverse problem to a finite-dimensional problem of CS type.
Sampling and Reconstruction of Sparse Signals in Shift-Invariant Spaces: Generalized Shannon's Theorem Meets Compressive Sensing
The SI samples are subsequently filtered by a discrete-time correction filter to reconstruct expansion coefficients of the observed signal.
