Related papers: DiffNMR: Diffusion Models for Nuclear Magnetic Res…
Conventional nuclear magnetic resonance (NMR) spectroscopy relies on acquiring signal from a macroscopic ensemble of molecules to gain information about molecular structure and dynamics. Transferring this technique to nanoscale sample sizes…
In this paper, we develop structure assisted nonnegative matrix factorization (NMF) methods for blind source separation of degenerate data. The motivation originates from nuclear magnetic resonance (NMR) spectroscopy, where a multiple…
Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI, enabling the mapping of multiple tissue properties from a single, accelerated scan. However, achieving accurate reconstructions remains challenging,…
Since its foundations, more than one hundred years ago, the field of structural biology has strived to understand and analyze the properties of molecules and their interactions by studying the structure that they take in 3D space. However,…
The task of deducing three-dimensional molecular configurations from their two-dimensional graph representations holds paramount importance in the fields of computational chemistry and pharmaceutical development. The rapid advancement of…
Diffusion generative models have emerged as a powerful framework for addressing problems in structural biology and structure-based drug design. These models operate directly on 3D molecular structures. Due to the unfavorable scaling of…
Atomic-scale magnetic field sensors based on nitrogen vacancy (NV) defects in diamonds are an exciting platform for nanoscale nuclear magnetic resonance (NMR) spectroscopy. The detection of NMR signals from a few zeptoliters to single…
Reconstructing visual stimuli from functional Magnetic Resonance Imaging fMRI enables fine-grained retrieval of brain activity. However, the accurate reconstruction of diverse details, including structure, background, texture, color, and…
Diffusion Magnetic Resonance Imaging (dMRI) is an imaging technique with exquisite sensitivity to the microstructural properties of heterogeneous media. The conventionally adopted acquisition schemes involving single pulsed field gradients…
Nuclear magnetic resonance (NMR) has enormous applications. Two-dimensional NMR is an essential technique to characterize correlations between nuclei and, hence, molecule structures. Towards the ultimate goal of single-molecule NMR,…
Diffusion-based super-resolution (SR) models have recently garnered significant attention due to their potent restoration capabilities. But conventional diffusion models perform noise sampling from a single distribution, constraining their…
Nuclear instance segmentation plays a vital role in disease diagnosis within digital pathology. However, limited labeled data in pathological images restricts the overall performance of nuclear instance segmentation. To tackle this…
Performing magnetic resonance imaging (MRI) reconstruction from under-sampled k-space data can accelerate the procedure to acquire MRI scans and reduce patients' discomfort. The reconstruction problem is usually formulated as a denoising…
Nuclear magnetic resonance (NMR) is a powerful method for determining the structure of molecules and proteins. While conventional NMR requires averaging over large ensembles, recent progress with single-spin quantum sensors has created the…
Brain cell structure and function reflect neurodevelopment, plasticity and ageing, and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to non-invasively…
Characterization of the molecular properties of surfaces under ambient or chemically reactive conditions is a fundamental scientific challenge. Moreover, many traditional analytical techniques used for probing surfaces often lack dynamic or…
Diffusion models (DMs) have emerged as powerful tools for modeling complex data distributions and generating realistic new samples. Over the years, advanced architectures and sampling methods have been developed to make these models…
Diffusion MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysical models is a challenging inverse problem, due to factors…
Nuclear Magnetic Resonance (NMR) spectroscopy has served as a powerful analytical tool for studying molecular structure and dynamics in chemistry and biology. However, the processing of raw data acquired from NMR spectrometers and…
Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. Local chemical complexity in compositionally complex alloys poses challenges for…