text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
methods other The kernel ABC nonparametric likelihood or ABC including ABC, outperforms synthetic ABC. | The nonparametric ABC outperforms other methods including ABC, kernel ABC or synthetic likelihood ABC. | 13,300 |
of data Synthetic our data test method. were inference and the used real to Bayesian | Synthetic data and real data were used to test the Bayesian inference of our method. | 13,301 |
computationally intractable is large data sets. for However, it | However, it is computationally intractable for large data sets. | 13,302 |
tackling work, introduce data multiresolution we sets. for persistent large this In homology | In this work, we introduce multiresolution persistent homology for tackling large data sets. | 13,303 |
method RNA fingerprints DNA further and molecules. We for topological from proposed demonstrate extracting the | We further demonstrate the proposed method for extracting topological fingerprints from DNA and RNA molecules. | 13,304 |
of linear commonly To problem variability, the averaging. smoothed address are before data group | To address the problem of variability, data are commonly smoothed before group linear averaging. | 13,305 |
smooth convex guarantees. problem an algorithm convergence a leads optimization with strong It to and | It leads to a smooth convex optimization problem and an algorithm with strong convergence guarantees. | 13,306 |
their needs attributes one associations. objects, such to a description and generate automatically, model To | To generate such a description automatically, one needs to model objects, attributes and their associations. | 13,307 |
object Conventional attribute methods require less and them strong annotation scalable. locations, making of | Conventional methods require strong annotation of object and attribute locations, making them less scalable. | 13,308 |
is This a Bayesian model. by achieved weakly introducing supervised novel non-parametric | This is achieved by introducing a novel weakly supervised non-parametric Bayesian model. | 13,309 |
knowledge framework hypothesis called virtues so present for formalising a graphs. We within | We present a framework for formalising so called hypothesis virtues within knowledge graphs. | 13,310 |
proposed by experiments the validate literature-based framework discovery. in We | We validate the proposed framework by experiments in literature-based discovery. | 13,311 |
and its experiments work demonstrated w.r.t. our The utility superiority have the of | The experiments have demonstrated the utility of our work and its superiority w.r.t. | 13,312 |
were Mass tested of screen-and-treat for achieving drug likelihood campaigns elimination. | Mass screen-and-treat drug campaigns were tested for likelihood of achieving elimination. | 13,313 |
of Conclusions reservoir. the density Low infectious portion a infections substantial comprise | Conclusions Low density infections comprise a substantial portion of the infectious reservoir. | 13,314 |
drugs control for Antimalarial a powerful are malaria and tool elimination. | Antimalarial drugs are a powerful tool for malaria control and elimination. | 13,315 |
setting. therapies can reduce combination widely campaign (ACTs) when transmission a in Artemisinin-based distributed | Artemisinin-based combination therapies (ACTs) can reduce transmission when widely distributed in a campaign setting. | 13,316 |
of killing to clinical gametocytes parasites data. asexual and calibrated Drug was | Drug killing of asexual parasites and gametocytes was calibrated to clinical data. | 13,317 |
We introduce an the between compatibility that a embedding. and function label measures a image | We introduce a function that measures the compatibility between an image and a label embedding. | 13,318 |
game computer terminals. system's in The runs | The game runs in computer system's terminals. | 13,319 |
sciences, is computational fundamental computer saliency Visual vision. a problem in including both and cognitive | Visual saliency is a fundamental problem in both cognitive and computational sciences, including computer vision. | 13,320 |
saliency of to coherence then refinement propose enhance the We a our method results. spatial | We then propose a refinement method to enhance the spatial coherence of our saliency results. | 13,321 |
large-scale more common (LGDM) decision making group are and more nowadays. Linguistic problems | Linguistic large-scale group decision making (LGDM) problems are more and more common nowadays. | 13,322 |
Distributed topic have signal during years. processing a become algorithms past the hot | Distributed signal processing algorithms have become a hot topic during the past years. | 13,323 |
attention One class special received that (PFs). of filters algorithms have particles are | One class of algorithms that have received special attention are particles filters (PFs). | 13,324 |
To the computer illustrate theoretical findings, tracking out target simulations carry a we problem. for | To illustrate the theoretical findings, we carry out computer simulations for a target tracking problem. | 13,325 |
attack a models two species. on between account predator's prey the These rates trade-off for | These models account for a trade-off between the predator's attack rates on two prey species. | 13,326 |
permanence strong lost. is at trade-offs, However, | However, at strong trade-offs, permanence is lost. | 13,327 |
coexistence. attractors loss this supporting there Despite of permanence, be can | Despite this loss of permanence, there can be attractors supporting coexistence. | 13,328 |
may however, coincide the These is at attractors, excluded. which predator with attractors | These attractors, however, may coincide with attractors at which the predator is excluded. | 13,329 |
Real bipartisanship on pairwise also congress US analyzing are in and DNA/time-series reported. alignments applications | Real applications on analyzing bipartisanship in US congress and pairwise DNA/time-series alignments are also reported. | 13,330 |
pipelines. Aligning is a to in a bioinformatics reference reads fundamental numerous sequence step | Aligning reads to a reference sequence is a fundamental step in numerous bioinformatics pipelines. | 13,331 |
positions the genome. reads about Simulation their source is accompanied information by in of | Simulation of reads is accompanied by information about their positions in the source genome. | 13,332 |
the evaluate by information mapper. then is used alignments produced to This | This information is then used to evaluate alignments produced by the mapper. | 13,333 |
successful alignments read are of reports containing created. statistics Finally, | Finally, reports containing statistics of successful read alignments are created. | 13,334 |
components. Futhermore, have software we an associated developed RNF package principal two containing | Futhermore, we have developed an associated software package RNF containing two principal components. | 13,335 |
tools CuReSim simulating of MIShmash Mason, etc.) one popular applies DwgSim, Art, (among read | MIShmash applies one of popular read simulating tools (among DwgSim, Art, Mason, CuReSim etc.) | 13,336 |
the RNF and generated reads into transforms format. | and transforms the generated reads into RNF format. | 13,337 |
using a reads evaluates simulated given RNF format. LAVEnder read in mapper then | LAVEnder evaluates then a given read mapper using simulated reads in RNF format. | 13,338 |
traditional to these solve with addition, methods. and unstable are In problems hard numerically | In addition, these problems are numerically unstable and hard to solve with traditional methods. | 13,339 |
the in embedding We low-dimensional consider k-nearest of problem Euclidean space. directed graphs neighbor unweighted, | We consider the problem of embedding unweighted, directed k-nearest neighbor graphs in low-dimensional Euclidean space. | 13,340 |
develop target and cells. dynamics model biophysical particles We a contact-mediated virus of involving | We develop a biophysical model of contact-mediated dynamics involving virus particles and target cells. | 13,341 |
approximation word derive we a for counts. normal Here such | Here we derive a normal approximation for such word counts. | 13,342 |
manifold. as is naturally on a clustering Grassmann problem This described | This is naturally described as a clustering problem on Grassmann manifold. | 13,343 |
tasks. computer in applications many have new The methods vision | The new methods have many applications in computer vision tasks. | 13,344 |
two penta-valued variants paper of neutrosophic for representation This presents entropy. | This paper presents two variants of penta-valued representation for neutrosophic entropy. | 13,345 |
at the targeted applications. primarily One PETS dataset, well-known surveillance of the few exceptions is | One of the few exceptions is the well-known PETS dataset, targeted primarily at surveillance applications. | 13,346 |
we are and here all of The provide passages. translations French, letters in key | The letters are all in French, and here we provide translations of key passages. | 13,347 |
as stored, at synapses. least Memories strong of patterns partly, are | Memories are stored, at least partly, as patterns of strong synapses. | 13,348 |
molecular for years how synapses maintain the strong can Given that turnover, persist? can memories | Given molecular turnover, how can synapses maintain strong for the years that memories can persist? | 13,349 |
postulate bistability maintains strong models synapses. Some that biochemical | Some models postulate that biochemical bistability maintains strong synapses. | 13,350 |
Bistability single has never synapses also empirically of been demonstrated. | Bistability of single synapses has also never been empirically demonstrated. | 13,351 |
it persistence. models to distributions is Thus important for memory simulate both and unimodal long-term | Thus it is important for models to simulate both unimodal distributions and long-term memory persistence. | 13,352 |
are clusters for years. competition, these stable With | With competition, these clusters are stable for years. | 13,353 |
applications tomatic intelligent recognition vehicle plate in systems. management license several Au- traffic has | Au- tomatic vehicle license plate recognition has several applications in intelligent traffic management systems. | 13,354 |
this system. phone mobile license describe we In paper, based, client-server architected, a plate recognition | In this paper, we describe a mobile phone based, client-server architected, license plate recognition system. | 13,355 |
in end end system architecture describe We to detail. the | We describe the end to end system architecture in detail. | 13,356 |
proposed lab environment. in been the system of the has working A prototype implemented | A working prototype of the proposed system has been implemented in the lab environment. | 13,357 |
a problem is of ill-posed online and The conversion problem. an to challenging offline script | The problem of offline to online script conversion is a challenging and an ill-posed problem. | 13,358 |
kinect system This using sensor. face a real-time presents recognition paper | This paper presents a real-time face recognition system using kinect sensor. | 13,359 |
speed GPU implemented observed. is using on are and significant opencl improvements The algorithm | The algorithm is implemented on GPU using opencl and significant speed improvements are observed. | 13,360 |
The mainly steps. composed is of algorithm three | The algorithm is mainly composed of three steps. | 13,361 |
the step First in is video to faces detect using jones all viola algorithm. | First step is to detect all faces in the video using viola jones algorithm. | 13,362 |
database on tracking The window generation face. using step is the online second a | The second step is online database generation using a tracking window on the face. | 13,363 |
classifier. train svm This feature used a is vector to | This feature vector is used to train a svm classifier. | 13,364 |
multiple recognition vector. faces modified Third involves of our step based feature on | Third step involves recognition of multiple faces based on our modified feature vector. | 13,365 |
development present of design camera and paper, this In an the we system. undersea | In this paper, we present the design and development of an undersea camera system. | 13,366 |
ROVs There our system are AUVs. comparing with two or using advantages main | There are two main advantages comparing our system with using ROVs or AUVs. | 13,367 |
can continuous undersea our the of monitoring First, habitat. system provide | First, our system can provide continuous monitoring of the undersea habitat. | 13,368 |
a system has low our cost. Second, hardware | Second, our system has a low hardware cost. | 13,369 |
Gabor depends This filtering. the dominant extraction using on of selection features | This selection depends on the extraction of dominant features using Gabor filtering. | 13,370 |
images images. and to as processes non-landmark classify landmark these method them then The | The method then processes these images to classify them as landmark and non-landmark images. | 13,371 |
highly the landmark. features The candidate number on classification performance depends of of the | The classification performance highly depends on the number of candidate features of the landmark. | 13,372 |
generalizations are Tensors or of multiarray matrices. data | Tensors or multiarray data are generalizations of matrices. | 13,373 |
researched. vectorizing multiarray clustering Subspace has been on extensively data based | Subspace clustering based on vectorizing multiarray data has been extensively researched. | 13,374 |
exploit complete However, structure not information. of tensorial vectorization data does | However, vectorization of tensorial data does not exploit complete structure information. | 13,375 |
clustering vectorization paper, we adopting this process. subspace propose In without a algorithm any | In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. | 13,376 |
a on novel heterogeneous Our based approach Tucker decomposition model. is | Our approach is based on a novel heterogeneous Tucker decomposition model. | 13,377 |
but closed-form updates. last mode the have All | All but the last mode have closed-form updates. | 13,378 |
latter to by two restaurant extending task The is the process accomplished Chinese dimensions. well-known | The latter task is accomplished by extending the well-known Chinese restaurant process to two dimensions. | 13,379 |
the approach. that issues performance affect We also future discuss this of | We also discuss issues that affect the future performance of this approach. | 13,380 |
vision represent models subspace Many data. algorithms employ computer to | Many computer vision algorithms employ subspace models to represent data. | 13,381 |
paper. manifold extending in explored on LRR this is The of possibility Grassmann | The possibility of extending LRR on Grassmann manifold is explored in this paper. | 13,382 |
proposed designed the is implemented. LRR solving model for algorithm Grassmannian new and A | A new algorithm for solving the proposed Grassmannian LRR model is designed and implemented. | 13,383 |
method outperforms The existing show a of experimental methods. number our results | The experimental results show our method outperforms a number of existing methods. | 13,384 |
novo assembly also challenging, De high-quality only data. computationally is not but requires | De novo assembly is not only computationally challenging, but also requires high-quality data. | 13,385 |
we implemented In we describe in approach this PopIns. paper, the | In this paper, we describe the approach we implemented in PopIns. | 13,386 |
for Image stack-based is HDR challenging. registration photography | Image registration for stack-based HDR photography is challenging. | 13,387 |
analytical model an function. Our is continues | Our model is an analytical continues function. | 13,388 |
features to semantics. in known inadequate be hand-crafted complex are analyzing video Traditional | Traditional hand-crafted features are known to be inadequate in analyzing complex video semantics. | 13,389 |
very video Based attained on on evaluations, are benchmarks. two the classification popular competitive results | Based on the evaluations, very competitive results are attained on two popular video classification benchmarks. | 13,390 |
by embedding features. a of the The graph linear is locally construction detection motivated | The graph construction is motivated by a locally linear embedding of the detection features. | 13,391 |
to decompose into global sub-problems. function propose We the node-wise objective | We propose to decompose the global objective function into node-wise sub-problems. | 13,392 |
opens the possibility it parallel of Moreover, implementation. | Moreover, it opens the possibility of parallel implementation. | 13,393 |
the units). recognition automatic for (sub-character primitives handwritten of are Experiments isolated conducted character | Experiments are conducted for the automatic recognition of isolated handwritten character primitives (sub-character units). | 13,394 |
using sequence protein k-means is information extracted optimised algorithm. this work In | In this work protein sequence information is extracted using optimised k-means algorithm. | 13,395 |
used of The swarm technique is optimisation particle optimisation one frequently method. the | The particle swarm optimisation technique is one of the frequently used optimisation method. | 13,396 |
current motif k-means extraction. In information the the PSO work is for used | In the current work the PSO k-means is used for motif information extraction. | 13,397 |
the structure protein acquired homogeneity the The motif of sequence. information is on based | The motif information acquired is based on the structure homogeneity of the protein sequence. | 13,398 |
can spike make A approximately simple trains. optimal network decisions given Bayes stochastic | A simple network can make approximately Bayes optimal decisions given stochastic spike trains. | 13,399 |
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