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hierarchical generative model

Satoshi Iso, Shotaro Shiba, Sumito Yokoo
Theoretical understanding of how a deep neural network (DNN) extracts features from input images is still unclear, but it is widely believed that the extraction is performed hierarchically through a process of coarse graining. It reminds us of the basic renormalization group (RG) concept in statistical physics. In order to explore possible relations between DNN and RG, we use the restricted Boltzmann machine (RBM) applied to an Ising model and construct a flow of model parameters (in particular, temperature) generated by the RBM...
May 2018: Physical Review. E
Wesley Cota, Géza Ódor, Silvio C Ferreira
Griffiths phases (GPs), generated by the heterogeneities on modular networks, have recently been suggested to provide a mechanism, rid of fine parameter tuning, to explain the critical behavior of complex systems. One conjectured requirement for systems with modular structures was that the network of modules must be hierarchically organized and possess finite dimension. We investigate the dynamical behavior of an activity spreading model, evolving on heterogeneous random networks with highly modular structure and organized non-hierarchically...
June 14, 2018: Scientific Reports
Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke
We explore classifier training for data sets with very few labels. We investigate this task using a neural network for nonnegative data. The network is derived from a hierarchical normalized Poisson mixture model with one observed and two hidden layers. With the single objective of likelihood optimization, both labeled and unlabeled data are naturally incorporated into learning. The neural activation and learning equations resulting from our derivation are concise and local. As a consequence, the network can be scaled using standard deep learning tools for parallelized GPU implementation...
June 12, 2018: Neural Computation
Juan Pablo Gomez, Scott K Robinson, Jason K Blackburn, José Miguel Ponciano
In this study we propose an extension of the N-mixture family of models that targets an improvement of the statistical properties of rare species abundance estimators when sample sizes are low, yet typical for tropical studies. The proposed method harnesses information from other species in an ecological community to correct each species' estimator. We provide guidance to determine the sample size required to estimate accurately the abundance of rare tropical species when attempting to estimate the abundance of single species...
February 2018: Methods in Ecology and Evolution
Gyula Kothencz, Kerstin Kulessa, Aynabat Anyyeva, Stefan Lang
The present study proposes a workflow to extract vegetation height for urban areas from Pléiades stereo and tri-stereo satellite imagery. The workflow was applied on a stereo image pair for Szeged, Hungary and on tri-stereo imagery for Salzburg, Austria. Digital surface models (DSMs) of the study areas were computed using the semi-global matching algorithm. Normalised digital surface models (nDSMs) were then generated. Objects of vegetation and non-vegetation were delineated based on the spectral information of the multispectral images by applying multi-resolution segmentation and support vector machine classifier...
2018: European Journal of Remote Sensing
Mathijs F J Mabesoone, Albert J Markvoort, Motonori Banno, Tomoko Yamaguchi, Floris Helmich, Yuki Naito, Eiji Yashima, Anja R A Palmans, Egbert Willem Meijer
Pathway complexity in supramolecular polymerization has recently sparked interest as a method to generate complex material behavior. The response of these systems relies on the existence of a metastable, kinetically trapped state. In this work, we show that strong switch-like behavior in supramolecular polymers can also be achieved through the introduction of competing aggregation pathways. This behavior is illustrated with the supramolecular polymerization of a porphyrin-based monomer at various concentrations, solvent compositions and temperatures...
June 10, 2018: Journal of the American Chemical Society
Felix Ratcliff, James Bartolome, Luke Macaulay, Sheri Spiegal, Michael D White
Ecological sites and state-and-transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively, little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California...
May 2018: Ecology and Evolution
Federica Torricelli, Davide Nicoli, Riccardo Bellazzi, Alessia Ciarrocchi, Enrico Farnetti, Valentina Mastrofilippo, Raffaella Zamponi, Giovanni Battista La Sala, Bruno Casali, Vincenzo Dario Mandato
Histological classification and staging are the gold standard for the prognosis of endometrial cancer (EC). However, in morphologically intermediate and doubtful cases this approach results largely insufficient, defining the need for better classification criteria. In this work we developed an algorithm that based on EC genetic alterations and in combination with the current histological classification, improves EC patients prognostic stratification, in particular in doubtful cases. A panel of 26 cancer related genes was analyzed in 89 EC patients and somatic functional mutations were investigated in association with different histology and outcome...
May 22, 2018: Oncotarget
Belén Fernández-Castilla, Marlies Maes, Lies Declercq, Laleh Jamshidi, S Natasha Beretvas, Patrick Onghena, Wim Van den Noortgate
It is common for the primary studies in meta-analyses to report multiple effect sizes, generating dependence among them. Hierarchical three-level models have been proposed as a means to deal with this dependency. Sometimes, however, dependency may be due to multiple random factors, and random factors are not necessarily nested, but rather may be crossed. For instance, effect sizes may belong to different studies, and, at the same time, effect sizes might represent the effects on different outcomes. Cross-classified random-effects models (CCREMs) can be used to model this nonhierarchical dependent structure...
June 5, 2018: Behavior Research Methods
Jeremy P Bennett, Claus P Haslauer, Martin Ross, Olaf A Cirpka
The spatial distribution of hydraulic properties in the subsurface controls groundwater flow and solute transport. However, many approaches to modeling these distributions do not produce geologically realistic results, and/or do not model the anisotropy of hydraulic conductivity caused by bedding structures in sedimentary deposits. We have developed a flexible object-based package for simulating hydraulic properties in the subsurface - the Hydrogeological Virtual Realities (HyVR) simulation package which implements a hierarchical modeling framework that takes into account geological rules about stratigraphic bounding surfaces and the geometry of specific sedimentary structures to generate realistic aquifer models, including full hydraulic-conductivity tensors...
June 3, 2018: Ground Water
Masabho P Milali, Maggy T Sikulu-Lord, Samson S Kiware, Floyd E Dowell, Richard J Povinelli, George F Corliss
BACKGROUND: Near infrared spectroscopy (NIRS) is a high throughput technique that measures absorbance of specific wavelengths of light by biological samples and uses this information to classify the age of lab-reared mosquitoes as younger or older than seven days with an average accuracy greater than 80%. For NIRS to estimate ages of wild mosquitoes, a sample of wild mosquitoes with known age in days would be required to train and test the model. Mark-release-recapture is the most reliable method to produce wild-caught mosquitoes of known age in days...
2018: PloS One
Anton V Chizhov, Artyom V Zefirov, Dmitry V Amakhin, Elena Yu Smirnova, Aleksey V Zaitsev
Seizures occur in a recurrent manner with intermittent states of interictal and ictal discharges (IIDs and IDs). The transitions to and from IDs are determined by a set of processes, including synaptic interaction and ionic dynamics. Although mathematical models of separate types of epileptic discharges have been developed, modeling the transitions between states remains a challenge. A simple generic mathematical model of seizure dynamics (Epileptor) has recently been proposed by Jirsa et al. (2014); however, it is formulated in terms of abstract variables...
May 31, 2018: PLoS Computational Biology
Yen-Yi Ho, Tien Nhu Vo, Haitao Chu, Xianghua Luo, Chap T Le
Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine...
July 2018: Statistical Methods in Medical Research
Gina Agarwal, Ricardo Angeles, Melissa Pirrie, Brent McLeod, Francine Marzanek, Jenna Parascandalo, Lehana Thabane
BACKGROUND: Low-income older adults who live in subsidized housing have higher mortality and morbidity. We aimed to determine if a community paramedicine program - in which paramedics provide health care services outside of the traditional emergency response - reduced the number of ambulance calls to subsidized housing for older adults. METHODS: We conducted an open-label pragmatic cluster-randomized controlled trial (RCT) with parallel intervention and control groups in subsidized apartment buildings for older adults...
May 28, 2018: CMAJ: Canadian Medical Association Journal, Journal de L'Association Medicale Canadienne
Ziao Tian, Wen Huang, Borui Xu, Xiuling Li, YongFeng Mei
Future advances in materials will be aided by improved dimensional control in fabrication of 3D hierarchical structures. Self-rolling technology provides additional degrees of freedom in 3D design by enabling an arbitrary rolling direction with controllable curvature. Here, we demonstrate that deterministic helical structures with variable rolling directions can be formed through releasing a strained nanomembrane patterned in a "utility knife" shape. The asymmetry of the membrane shape provides anisotropic driving force generated by the disparity between the etching rates along different sides in this asymmetric shape...
May 25, 2018: Nano Letters
Li Wenliang, Aaron R Seitz
Understanding visual perceptual learning (VPL) has become increasingly more challenging as new phenomena are discovered with novel stimuli and training paradigms. While existing models aid our knowledge of critical aspects of VPL, the connections shown by these models between behavioral learning and plasticity across different brain areas are typically superficial. Most models explain VPL as readout from simple perceptual representations to decision areas and are not easily adaptable to explain new findings...
May 23, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Mingche Liu, Oluwaseun Adebayo Bamodu, Kuang-Tai Kuo, Wei-Hwa Lee, Yen-Kuang Lin, Alexander T H Wu, Hsiao M, Yew-Min Tzeng, Chi-Tai Yeh, Jo-Ting Tsai
The hierarchical tumor propagation or cancer stem cells (CSCs) model of carcinogenesis postulates that like physiologic adult stem cell (ASC), the CSCs positioned at the apex of any tumor population form the crux of tumor evolution with a constitutive regenerative capacity and differentiation potential. The propagation and recurrence of the characteristically heterogeneous and therapy-resistant hepatocellular carcinoma (HCC), adds to accumulating evidence to support this CSCs model. Based on the multi-etiologic basis of HCC formation which among others, focuses on the disruption of the canonical Wnt signaling pathway, this study evaluated the role of cembrane-type phytochemical, Ovatodiolide, in the modulation of the Wnt/[Formula: see text]-catenin pathway, and its subsequent effect on liver CSCs' activities...
May 24, 2018: American Journal of Chinese Medicine
Ning Huang, Hannah Drake, Jialuo Li, Jiangdong Pang, Ying Wang, Shuai Yuan, Qi Wang, Peiyu Cai, Junsheng Qin, Hong-Cai Zhou
The development of new types of porous composite materials is of great significance owing to their potentially improved performance over those of individual components and extensive applications in separation, energy storage, and heterogeneous catalysis. In this work, we integrated mesoporous metal-organic frameworks (MOFs) with macroporous melamine foam (MF) using a one-pot process, generating a series of MOF/MF composite materials with preserved crystallinity, hierarchical porosity, and increased stability over that of melamine foam...
May 18, 2018: Angewandte Chemie
Susanne G Mueller
Recent findings in AD models but also human patients suggest that amyloid can cause intermittent neuronal hyperactivity. The overall goal of this study was to use dynamic fMRI analysis combined with graph analysis to a) characterize the graph analytical signature of two types of intermittent hyperactivity (spike-like (spike) and hypersynchronus-like (synchron)) in simulated data and b) to attempt to identify one of these signatures in task-free fMRIs of cognitively intact subjects (CN) with or without increased brain amyloid...
May 16, 2018: Brain Imaging and Behavior
Keisuke Yamazaki
Hierarchical learning models, such as mixture models and Bayesian networks, are widely employed for unsupervised learning tasks, such as clustering analysis. They consist of observable and latent variables, which represent the given data and their underlying generation process, respectively. It has been pointed out that conventional statistical analysis is not applicable to these models, because redundancy of the latent variable produces singularities in the parameter space. In recent years, a method based on algebraic geometry has allowed us to analyze the accuracy of predicting observable variables when using Bayesian estimation...
March 13, 2018: Neural Networks: the Official Journal of the International Neural Network Society
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