Results 81 to 90 of about 29,999,610 (319)
Configuration and intercomparison of deep learning neural models for statistical downscaling
Geoscientific Model Development, 2019 . Deep learning techniques (in particular convolutional neural networks, CNNs) have recently emerged as a promising approach for statistical downscaling due to their ability to learn spatial features from huge spatiotemporal datasets.
J. Baño-Medina +2 more
semanticscholar +1 more source
Statistical Models for Company Growth [PDF]
SSRN Electronic Journal, 2003 Minor changes, submitted to Physica ...
Wyart, Matthieu, Bouchaud, Jean-Philippe
openaire +6 more sources
FEBS Letters, EarlyView.Mutations in the C9orf72 gene represent the most common genetic cause of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease. Using patient‐derived neurons and C. elegans models, we find that the nucleoporin Nup107 is dysregulated in C9orf72‐associated ALS. Conversely, reducing Nup107 levels mitigates disease‐related changes.
Saygın Bilican +7 more
wiley +1 more source
Statistical and Dynamic Models of Charge Balance Functions
, 2004 Charge balance functions, which identify balancing particle-antiparticle pairs on a statistical basis, have been shown to be sensitive to whether hadronization is delayed by several fm/c in relativistic heavy ion collisions.
B. Tomásik +11 more
core +1 more source
Statistical Models and Invariance
The Annals of Mathematical Statistics, 1967 Brillinger [2] gives necessary and sufficient conditions for a model to be invariant under a Lie group of transformations. The problems that can be handled by his conditions are surveyed, and found effectively to be restricted to one-dimensional problems amendable to Lindley's [8] method and to problems connected with conflicts between Bayes' and ...
openaire +3 more sources
Chaos, Solitons & Fractals, 2006 The p-model is a mathematical construction largely applied in physics to construct intermittent distributions on a real interval and in general to study diadic branching processes (cascades). The model produces a hierarchy of Id distributions u((n)) with n = 0, 1, 2..., referred to as generations, that may be used to mimic natural irregular signals at ...
Materassi M., Wernik A., Yordanova E.
openaire +3 more sources
FEBS Letters, EarlyView.Single‐cell RNA sequencing reveals an opposite role of SLPI in basal tumors based on metastatic spread, along with shared activation of specific regulons in cancer cells and mature luminal lactocytes, as well as downregulation of MALAT1 and NEAT1 in the latter.
Pietro Ancona +4 more
wiley +1 more source
Break-up fragment topology in statistical multifragmentation models
, 2009 Break-up fragmentation patterns together with kinetic and configurational energy fluctuations are investigated in the framework of a microcanonical model with fragment degrees of freedom over a broad excitation energy range.
Ad. R. Raduta, D. H. E. Gross
core +3 more sources
Wastewater Quality Estimation through Spectrophotometry-Based Statistical Models
Sensors, 2020 Local administrations are increasingly demanding real-time continuous monitoring of pollution in the sanitation system to improve and optimize its operation, to comply with EU environmental policies and to reach European Green Deal targets.
Daniel Carreres-Prieto +3 more
doaj +1 more source
Theory of Statistical Inference
Journal of the American Statistical AssociationStatistical inference is about figuring out what data are telling us about the world. We gather data related to some question of interest and construct a model of how the data could have been generated.
Somabha Mukherjee
semanticscholar +1 more source