Towards Building Deep Networks with Bayesian Factor Graphs

We propose a Multi-Layer Network based on the Bayesian framework of the Factor Graphs in Reduced Normal Form (FGrn) applied to a two-dimensional lattice. The Latent Variable Model (LVM) is the basic building block of a quadtree hierarchy built on top of a bottom layer of random variables that represent pixels of an image, a feature map, or more generally a collection of spatially distributed discrete variables. The multi-layer architecture implements a hierarchical data representation that, via belief propagation, can be used for learning and inference. Typical uses are pattern completion, correction and classification. The FGrn paradigm provides great flexibility and modularity and appears as a promising candidate for building deep networks: the system can be easily extended by introducing new and different (in cardinality and in type) variables. Prior knowledge, or supervised information, can be introduced at different scales. The FGrn paradigm provides a handy way for building all kinds of architectures by interconnecting only three types of units: Single Input Single Output (SISO) blocks, Sources and Replicators. The network is designed like a circuit diagram and the belief messages flow bidirectionally in the whole system. The learning algorithms operate only locally within each block. The framework is demonstrated in this paper in a three-layer structure applied to images extracted from a standard data set.Comment: Submitted for journal publicatio

Estimation of protein folding probability from equilibrium simulations

The assumption that similar structures have similar folding probabilities ($p_{fold}$) leads naturally to a procedure to evaluate $p_{fold}$ for every snapshot saved along an equilibrium folding-unfolding trajectory of a structured peptide or protein. The procedure utilizes a structurally homogeneous clustering and does not require any additional simulation. It can be used to detect multiple folding pathways as shown for a three-stranded antiparallel $\beta$-sheet peptide investigated by implicit solvent molecular dynamics simulations.Comment: 7 pages, 4 figures, supplemetary material

The Influence of N14(e-,nu)C14(alpha,gamma)O18 reaction on the He-Ignition in Degenerate Physical Conditions

The importance of NCO chain on the onset of the He-flash in degenerate physical conditions has been reevaluated. We find that low-mass, metal-rich (Z $\ge$ 0.001) structures climbing the Red Giant Branch do never attain the physical conditions suitable for the onset of this chain, while at lower metallicities the energy contribution provided by NCO reaction is too low to affect the onset of the central He-flash. At the same time, our evolutionary models suggest that for a Carbon-Oxygen White Dwarf of mass M_{WD}=0.6 M_sun accreting He-rich matter, directly or as a by-product of an overlying H-burning shell, at rates suitable for a dynamical He-flash, the NCO energy contribution is not able to keep hot enough the He-shell and in turn to avoid the occurrence of a strong electron degeneracy and the ensuing final explosion.Comment: 15 pages, 3 tables, 10 figure, to appear in Ap

Education, redistributive taxation and confidence

"We consider redistributional taxation between people with and without human capital if education is endogenous and if individuals differ in their perceptions about own ability. Those who see their ability as low like redistributive taxation because of the transfers it generates. Those who see their ability as high may also like redistributive taxation because it stops other people receiving education and increases the quasi rents on their own human capital. It is surprising that this rather indirect effect can overcompensate them for the income loss from taxation and make the overconfident want higher taxes than the less confident do. The results, however, turn out to be in line with empirical evidence on the desired amount of redistribution among young individuals." (author's abstract)"Betrachtet wird die Steuerumverteilung zwischen Individuen mit hohem und niedrigem Ausbildungsstand, wobei angenommen wird, dass Bildung endogen ist und die Individuen unterschiedliche Wahrnehmungen über ihre eigenen Fähigkeiten haben. Diejenigen, die ihre Fähigkeiten niedrig einschätzen bevorzugen eine Steuerumverteilung, da durch sie eine (Vermögens-)Übertragung erzeugt wird. Diejenigen, die ihre Fähigkeiten sehr hoch einschätzen bevorzugen ebenfalls eine Steuerumverteilung, da hierdurch andere Individuen davon abgehalten werden, Bildung zu erwerben und somit die Quasi-Rechte der ersteren aus ihrer Ausbildung erhöht werden. Dieser indirekte Effekt kann den Einkommensverlust durch Steuern überkompensieren. Die Bestausgebildesten fordern sogar höhere Steuern als die Individuen mit niedrigerem Bildungsniveau. Die Ergebnisse entsprechen den empirisch beobachteten gewünschten Umverteilungsbeträgen unter jungen Individuen." (Autorenreferat

Imagery-mediated verbal learning depends on vividness–familiarity interactions: The possible role of dualistic resting state network activity interference

Using secondary database analysis, we tested whether the (implicit) familiarity of eliciting noun-cues and the (explicit) vividness of corresponding imagery exerted additive or interactive influences on verbal learning, as measured by the probability of incidental noun recall and image latency times (RTs). Noun-cues with incongruent levels of vividness and familiarity (high/low; low/high, respectively) at encoding were subsequently associated at retrieval with the lowest recall probabilities, while noun-cues related with congruent levels (high/high; low/low) were associated with higher recall probabilities. RTs in the high vividness and high familiarity grouping were significantly faster than all other subsets (low/low, low/high, high/low) which did not significantly differ among each other. The findings contradict: (1) associative theories predicting positive monotonic relationships between memory strength and learning; and (2) non-monotonic plasticity hypothesis (NMPH), aiming at generalizing the non-monotonic relationship between a neuron’s excitation level and its synaptic strength to broad neural networks. We propose a dualistic neuropsychological model of memory consolidation that mimics the global activity in two large resting-state networks (RSNs), the default mode network (DMN) and the task-positive-network (TPN). Based on this model, we suggest that incongruence and congruence between vividness and familiarity reflect, respectively, competition and synergy between DMN and TPN activity. We argue that competition or synergy between these RSNs at the time of stimulus encoding disproportionately influences long term semantic memory consolidation in healthy controls. These findings could assist in developing neurophenomenological markers of core memory deficits currently hypothesized to be shared across multiple psychopathological conditions

Unsolved Problems about Supernovae

A number of unsolved problems and open questions about the nature and the properties of supernovae are identified and briefly discussed. Some suggestions and directions toward possible solutions are also considered.Comment: 7 pages, Proceedings of 'Probing Stellar Populations out to the Distant Universe', Cefalu, Italy, Sep 7-19, 2008, AIP Conf. Proc. Serie

Advances on GRB as cosmological tools

Several interesting correlations among Gamma Ray Bursts (GRB) prompt and afterglow properties have been found in the recent years. Some of these correlations have been proposed also to standardize GRB energetics to use them as standard candles in constraining the expansion history of the universe up to z>6. However, given the still unexplained nature of most of these correlations, only the less scattered correlations can be used for constraining the cosmological parameters. The updated E_peak-E_gamma correlation is presented. Caveats of alternative methods of standardizing GRB energetics are discussed.Comment: 8 parges, AIP conf. proc. "Probing stellar populations out to the distant universe, Cefalu' 2008" Vol. 1111, pp. 579-58

The formation and evolution of early-type galaxies : solid results and open questions

The most recent results and some of the open key questions on the evolution of early-type galaxies are reviewed in the general cosmological context of massive galaxy formation.Comment: 8 pages, invited review at the workshop "Probing Stellar Populations out to the Distant Universe", Cefalu` (Italy), September 7 - 19, 200

Spectral libraries and their uncertainties

Libraries of stellar spectra are fundamental tools in the study of stellar populations and in automatic determination of atmospheric parameters for large samples of observed stars. In the context of the present volume, here I give an overview of the current status of stellar spectral libraries from the perspective of stellar population modeling: what we have currently available, how good they are, and where we need further improvement