Deep bayesian network for visual question generation

Generating natural questions from an image is a semantic task that requires using vision and language modalities to learn multimodal representations. Images can have multiple visual and language cues such as places, captions, and tags. In this paper, we propose a principled deep Bayesian learning framework that combines these cues to produce natural questions. We observe that with the addition of more cues and by minimizing uncertainty in the among cues, the Bayesian network becomes more confident. We propose a Minimizing Uncertainty of Mixture of Cues (MUMC), that minimizes uncertainty present in a mixture of cues experts for generating probabilistic questions. This is a Bayesian framework and the results show a remarkable similarity to natural questions as validated by a human study. We observe that with the addition of more cues and by minimizing uncertainty among the cues, the Bayesian framework becomes more confident. Ablation studies of our model indicate that a subset of cues is inferior at this task and hence the principled fusion of cues is preferred. Further, we observe that the proposed approach substantially improves over state-of-the-art benchmarks on the quantitative metrics (BLEU-n, METEOR, ROUGE, and CIDEr). Here we provide project link for Deep Bayesian VQG \url{https://delta-lab-iitk.github.io/BVQG/}Comment: WACV-2020 (Accepted

The Multifragmentation Freeze--Out Volume in Heavy Ion Collisions

The reduced velocity correlation function for fragments from the reaction Fe + Au at 100 A~MeV bombarding energy is investigated using the dynamical--statistical approach QMD+SMM and compared to experimental data to extract the Freeze--Out volume assuming simultaneous multifragmentation.Comment: 8 pages; 3 uuencoded figures available with figures command, LateX, UCRL-J-1157

Antiproton Production in p+Ap+A Collisions at AGS Energies

Inclusive and semi-inclusive measurements are presented for antiproton ($\bar{p}$) production in proton-nucleus collisions at the AGS. The inclusive yields per event increase strongly with increasing beam energy and decrease slightly with increasing target mass. The $\bar{p}$ yield in 17.5 GeV/c p+Au collisions decreases with grey track multiplicity, $N_g$, for $N_g>0$, consistent with annihilation within the target nucleus. The relationship between $N_g$ and the number of scatterings of the proton in the nucleus is used to estimate the $\bar{p}$ annihilation cross section in the nuclear medium. The resulting cross section is at least a factor of five smaller than the free $\bar{p}-p$ annihilation cross section when assuming a small or negligible formation time. Only with a long formation time can the data be described with the free $\bar{p}-p$ annihilation cross section.Comment: 8 pages, 6 figure

Semi-Inclusive Lambda and Kshort Production in p-Au Collisions at 17.5 GeV/c

The first detailed measurements of the centrality dependence of strangeness production in p-A collisions are presented. Lambda and Kshort dn/dy distributions from 17.5 GeV/c p-Au collisions are shown as a function of "grey" track multiplicity and the estimated number of collisions, nu, made by the proton. The nu dependence of the Lambda yield deviates from a scaling of p-p data by the number of participants, increasing faster than this scaling for nu<=5 and saturating for larger nu. A slower growth in Kshort multiplicity with nu is observed, consistent with a weaker nu dependence of K-Kbar production than Y-K production.Comment: 5 pages, 3 figures, formatted with RevTex, current version has enlarged figure catpion

Strangeness Enhancement in p+Ap+A and S+AS+A Interactions at SPS Energies

The systematics of strangeness enhancement is calculated using the HIJING and VENUS models and compared to recent data on $\,pp\,$, $\,pA\,$ and $\,AA\,$ collisions at CERN/SPS energies ($200A\,\, GeV\,$). The HIJING model is used to perform a {\em linear} extrapolation from $pp$ to $AA$. VENUS is used to estimate the effects of final state cascading and possible non-conventional production mechanisms. This comparison shows that the large enhancement of strangeness observed in $S+Au$ collisions, interpreted previously as possible evidence for quark-gluon plasma formation, has its origins in non-equilibrium dynamics of few nucleon systems. % Strangeness enhancement %is therefore traced back to the change in the production dynamics %from $pp$ to minimum bias $pS$ and central $SS$ collisions. A factor of two enhancement of $\Lambda^{0}$ at mid-rapidity is indicated by recent $pS$ data, where on the average {\em one} projectile nucleon interacts with only {\em two} target nucleons. There appears to be another factor of two enhancement in the light ion reaction $SS$ relative to $pS$, when on the average only two projectile nucleons interact with two target ones.Comment: 29 pages, 8 figures in uuencoded postscript fil