A Context-aware Attention Network for Interactive Question Answering

Neural network based sequence-to-sequence models in an encoder-decoder framework have been successfully applied to solve Question Answering (QA) problems, predicting answers from statements and questions. However, almost all previous models have failed to consider detailed context information and unknown states under which systems do not have enough information to answer given questions. These scenarios with incomplete or ambiguous information are very common in the setting of Interactive Question Answering (IQA). To address this challenge, we develop a novel model, employing context-dependent word-level attention for more accurate statement representations and question-guided sentence-level attention for better context modeling. We also generate unique IQA datasets to test our model, which will be made publicly available. Employing these attention mechanisms, our model accurately understands when it can output an answer or when it requires generating a supplementary question for additional input depending on different contexts. When available, user's feedback is encoded and directly applied to update sentence-level attention to infer an answer. Extensive experiments on QA and IQA datasets quantitatively demonstrate the effectiveness of our model with significant improvement over state-of-the-art conventional QA models.Comment: 9 page

Bayesian Learning of Sum-Product Networks

Sum-product networks (SPNs) are flexible density estimators and have received significant attention due to their attractive inference properties. While parameter learning in SPNs is well developed, structure learning leaves something to be desired: Even though there is a plethora of SPN structure learners, most of them are somewhat ad-hoc and based on intuition rather than a clear learning principle. In this paper, we introduce a well-principled Bayesian framework for SPN structure learning. First, we decompose the problem into i) laying out a computational graph, and ii) learning the so-called scope function over the graph. The first is rather unproblematic and akin to neural network architecture validation. The second represents the effective structure of the SPN and needs to respect the usual structural constraints in SPN, i.e. completeness and decomposability. While representing and learning the scope function is somewhat involved in general, in this paper, we propose a natural parametrisation for an important and widely used special case of SPNs. These structural parameters are incorporated into a Bayesian model, such that simultaneous structure and parameter learning is cast into monolithic Bayesian posterior inference. In various experiments, our Bayesian SPNs often improve test likelihoods over greedy SPN learners. Further, since the Bayesian framework protects against overfitting, we can evaluate hyper-parameters directly on the Bayesian model score, waiving the need for a separate validation set, which is especially beneficial in low data regimes. Bayesian SPNs can be applied to heterogeneous domains and can easily be extended to nonparametric formulations. Moreover, our Bayesian approach is the first, which consistently and robustly learns SPN structures under missing data.Comment: NeurIPS 2019; See conference page for supplemen

Origami Multistabilty: From Single Vertices to Metasheets

We explore the surprisingly rich energy landscape of origami-like folding planar structures. We show that the configuration space of rigid-paneled degree-4 vertices, the simplest building blocks of such systems, consists of at least two distinct branches meeting at the flat state. This suggests that generic vertices are at least bistable, but we find that the nonlinear nature of these branches allows for vertices with as many as five distinct stable states. In vertices with collinear folds and/or symmetry, more branches emerge leading to up to six stable states. Finally, we introduce a procedure to tile arbitrary 4-vertices while preserving their stable states, thus allowing the design and creation of multistable origami metasheets.Comment: For supplemental movies please visit http://www.lorentz.leidenuniv.nl/~chen/multisheet

Variability and trend of the north west Australia rainfall: observations and coupled climate modeling

Since 1950, there has been an increase in rainfall over North West Australia (NWA), occurring mainly during the Southern Hemisphere (SH) summer season. A recent study using 20th century multi-member ensemble simulations in a global climate model forced with and without increasing anthropogenic aerosols suggests that the rainfall increase is attributable to increasing Northern Hemisphere aerosols. The present study investigates the dynamics of the observed trend toward increased rainfall and compares the observed trend with that generated in the model forced with increasing aerosols. We find that the observed positive trend in rainfall is projected onto two modes of variability. The first mode is associated with an anomalously low mean sea level pressure (MSLP) off NWA instigated by the enhanced sea surface temperature (SST) gradients towards the coast. The associated cyclonic flows bring high moisture air to northern Australia, leading to an increase in rainfall. The second mode is associated with an anomalously high MSLP over much of the Australian continent; the anticyclonic circulation pattern with northwesterly flows west of 130°E and generally opposite flows in northeastern Australia, determine that when rainfall is anomalously high, west of 130oE, rainfall is anomalously low east of this longitude. The sum of the upward trends in these two modes compares well to the observed increasing trend pattern. The modeled rainfall trend, however, is generated by a different process. The model suffers from an equatorial cold-tongue bias: the tongue of anomalies associated with El Niño-Southern Oscillation extends too far west into the eastern Indian Ocean. Consequently, there is an unrealistic relationship in the SH summer between Australian rainfall and eastern Indian Ocean SST: the rise in SST is associated with an increasing rainfall over NWA. In the presence of increasing aerosols, a significant SST increase occurs in the eastern tropical Indian Ocean. As a result, the modeled rainfall increase in the presence of aerosol forcing is accounted for by these unrealistic relationships. It is not clear whether, in a model without such defects, the observed trend can be generated by increasing aerosols. Thus, the impact of aerosols on Australian rainfall remains an open question

Learning Temporal Transformations From Time-Lapse Videos

Based on life-long observations of physical, chemical, and biologic phenomena in the natural world, humans can often easily picture in their minds what an object will look like in the future. But, what about computers? In this paper, we learn computational models of object transformations from time-lapse videos. In particular, we explore the use of generative models to create depictions of objects at future times. These models explore several different prediction tasks: generating a future state given a single depiction of an object, generating a future state given two depictions of an object at different times, and generating future states recursively in a recurrent framework. We provide both qualitative and quantitative evaluations of the generated results, and also conduct a human evaluation to compare variations of our models.Comment: ECCV201

Genomic characterisation of an endometrial pathogenic <i>Escherichia coli</i> strain reveals the acquisition of genetic elements associated with extra-intestinal pathogenicity

&lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Strains of &lt;i&gt;Escherichia coli&lt;/i&gt; cause a wide variety of intestinal and extra-intestinal diseases in both humans and animals, and are also often found in healthy individuals or the environment. Broadly, a strong phylogenetic relationship exists that distinguishes most &lt;i&gt;E. Coli&lt;/i&gt; causing intestinal disease from those that cause extra-intestinal disease, however, isolates within a recently described subclass of Extra-Intestinal Pathogenic &lt;i&gt;E. Coli&lt;/i&gt; (ExPEC), termed endometrial pathogenic &lt;i&gt;E. Coli&lt;/i&gt;, tend to be phylogenetically distant from the vast majority of characterised ExPECs, and more closely related to human intestinal pathogens. In this work, we investigate the genetic basis for ExPEC infection in the prototypic endometrial pathogenic &lt;i&gt;E. Coli&lt;/i&gt; strain MS499.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt;&lt;p&gt;&lt;/p&gt; By investigating the genome of MS499 in comparison with a range of other E. coli sequences, we have discovered that this bacterium has acquired substantial lengths of DNA which encode factors more usually associated with ExPECs and less frequently found in the phylogroup relatives of MS499. Many of these acquired factors, including several iron acquisition systems and a virulence plasmid similar to that found in several ExPECs such as APEC O1 and the neonatal meningitis &lt;i&gt;E. Coli&lt;/i&gt; S88, play characterised roles in a variety of typical ExPEC infections and appear to have been acquired recently by the evolutionary lineage leading to MS499.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Taking advantage of the phylogenetic relationship we describe between MS499 and several other closely related &lt;i&gt;E. Coli&lt;/i&gt; isolates from across the globe, we propose a step-wise evolution of a novel clade of sequence type 453 ExPECs within phylogroup B1, involving the recruitment of ExPEC virulence factors into the genome of an ancestrally non-extraintestinal &lt;i&gt;E. Coli&lt;/i&gt;, which has repurposed this lineage with the capacity to cause extraintestinal disease. These data reveal the genetic components which may be involved in this phenotype switching, and argue that horizontal gene exchange may be a key factor in the emergence of novel lineages of ExPECs.&lt;p&gt;&lt;/p&gt

Reaction-Diffusion Processes as Physical Realizations of Hecke Algebras

We show that the master equation governing the dynamics of simple diffusion and certain chemical reaction processes in one dimension give time evolution operators (Hamiltonians) which are realizations of Hecke algebras. In the case of simple diffusion one obtains, after similarity transformations, reducible hermitian representations while in the other cases they are non-hermitian and correspond to supersymmetric quotients of Hecke algebras.Comment: Latex, 6 pages, BONN-HE-93.1