Related papers: Extraction of N* information from the limited p(ga…
The quality of numerical reconstructions for unknown parameters in inverse problems depends fundamentally on the selection of experimental data. To ensure a robust reconstruction, it is crucial to select data that are sensitive to the…
An effective Lagrangian model in a coupled channels framework is applied to extract nucleon resonance parameters. In the K-matrix approximation, we simultaneously analyze all the available data for the transitions from pi N to five possible…
Our world is ambiguous and this is reflected in the data we use to train our algorithms. This is particularly true when we try to model natural processes where collected data is affected by noisy measurements and differences in measurement…
Neural networks can be used as surrogates for PDE models. They can be made physics-aware by penalizing underlying equations or the conservation of physical properties in the loss function during training. Current approaches allow to…
A new procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Novelties are usage of the Latin Hypercube Sampling method for the generation of…
We report an interpretation method for deep learning models that allows us to handle high-dimensional spectral data in materials science. The proposed method uses feature extraction and clustering analysis to categorize materials into…
We present an autodifferentiable rejection sampling algorithm termed Rejection Sampling with Autodifferentiation (RSA). In conjunction with reweighting, we show that RSA can be used for efficient parameter estimation and model exploration.…
Radiative capture of the K-minus by the deuteron as a reaction for measurement of the Lambda-neutron scattering lengths. The use of spin information to separate the singlet and triplet scattering lengths is treated.
The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing…
The interaction of Lambda*=Lambda(1405) with a nucleon is studied from the viewpoint of chiral dynamics. We construct the coordinate space Lambda* N potential in the meson-exchange picture, which serves as a fundamental ingredient for the…
Histogram-based template fits are the main technique used for estimating parameters of high energy physics Monte Carlo generators. Parametrized neural network reweighting can be used to extend this fitting procedure to many dimensions and…
In a previous publication [Atomic Data and Nuclear Data Tables 75, 1 (2000)], we had given seven parameter analytical fits to theoretical reaction rates derived from nuclear cross sections calculated in the statistical model…
The advent of large scale, high-throughput genomic screening has introduced a wide range of tests for diagnostic purposes. Prominent among them are tests using miRNA expression levels. Genomics and proteomics now provide expression levels…
Personalized diagnoses have not been possible due to sear amount of data pathologists have to bear during the day-to-day routine. This lead to the current generalized standards that are being continuously updated as new findings are…
Multi-model inference covers a wide range of modern statistical applications such as variable selection, model confidence set, model averaging and variable importance. The performance of multi-model inference depends on the availability of…
The promise and limitations of studying nuclear structure and reactions using (e,e'p) reactions are discussed. A(e,e'p)A-1 reactions on complex nuclei are used to test new relativistic mean-field calculations and their ingredients such as…
Hedging in the presence of transaction costs leads to complex optimization problems. These problems typically lack closed-form solutions, and their implementation relies on numerical methods that provide hedging strategies for specific…
We study the photoproduction of the $\Lambda(1405)$ and $\Sigma(1400)$ hyperon resonances, the latter of which is not a well established state. We evaluate the $s$-, $t$- and $u$-channel diagrams in the Born approximation by employing the…
This study aims at understanding the nature of measured data on the rapidity spectra of some heavy baryons [$\Lambda$, $\Lambda$bar, $\Xi^-$ & $\Xi$bar$^+$] produced in the nuclear collisions at some modestly high energies. Furthermore, our…
Understanding molecular structure, dynamics, and reactivity requires bridging processes that occur across widely separated time scales. Conventional molecular dynamics simulations provide atomistic resolution, but their femtosecond time…