text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
flexible non-parametric Bayesian Tree is density estimation. P\'{o}lya a model (OPT) Optional for | Optional P\'{o}lya Tree (OPT) is a flexible non-parametric Bayesian model for density estimation. | 8,300 |
inference its OPT merits, challenging. for computation the is Despite | Despite its merits, the computation for OPT inference is challenging. | 8,301 |
two improvements simulations. the these of demonstrate using We performance | We demonstrate the performance of these two improvements using simulations. | 8,302 |
are large In clusters. systems, many spatially sensory transmembrane organized in receptors | In many sensory systems, transmembrane receptors are spatially organized in large clusters. | 8,303 |
multiple of may and facilitate stimuli. arrangement Such signal amplification integration the | Such arrangement may facilitate signal amplification and the integration of multiple stimuli. | 8,304 |
in receptor activity fluctuations quantified been experimentally. have Large | Large fluctuations in receptor activity have been quantified experimentally. | 8,305 |
That important. choice means, may learning methods of dictionary not be the | That means, the choice of dictionary learning methods may not be important. | 8,306 |
to different closure moment different assumptions lead mean-field systems. Three three | Three different moment closure assumptions lead to three different mean-field systems. | 8,307 |
full the for numerical This with biologically simulations parameter reasonable confirmed network of values. is | This is confirmed with numerical simulations of the full network for biologically reasonable parameter values. | 8,308 |
regression. This data advanced such requires functional methods, of analysis the use as | This requires the use of advanced data analysis methods, such as functional regression. | 8,309 |
an experimental methodology vineyards. a is to design case in applied study involving French The | The methodology is applied to a case study involving an experimental design in French vineyards. | 8,310 |
well are genericity robustness. discussed, and the as as method results The | The results are discussed, as well as the method genericity and robustness. | 8,311 |
primary the thinking Like faculties of today, were individuals. reasoning and | Like today, reasoning and thinking were the primary faculties of individuals. | 8,312 |
cortex Its smaller the brain convoluted. less was was and apparently | Its brain was smaller and the cortex was apparently less convoluted. | 8,313 |
rapid a it that, Despite proliferated at pace. | Despite that, it proliferated at a rapid pace. | 8,314 |
running Endurance sapiens. Homo the to led of emergence | Endurance running led to the emergence of Homo sapiens. | 8,315 |
such searched, minimally that an its filter gaussian. inverse Hence, is output is | Hence, an inverse filter is searched, such that its output is minimally gaussian. | 8,316 |
of signal. the use We the non-gaussianity measure the of a as kurtosis | We use the kurtosis as a measure of the non-gaussianity of the signal. | 8,317 |
kurtosis maximum deconvolving A the is of filter function coefficients the as of searched. a | A maximum of the kurtosis as a function of the deconvolving filter coefficients is searched. | 8,318 |
may signal This applied the original obtain be the to undistorted distorted filter signal. to | This filter may be applied to the distorted signal to obtain the original undistorted signal. | 8,319 |
a framework, its Dirichlet solution for this process. on variational Based provides full the | Based on this framework, its provides a full variational solution for the Dirichlet process. | 8,320 |
that computationally to numerical very efficient when results compared the method is show The MCMC. | The numerical results show that the method is very computationally efficient when compared to MCMC. | 8,321 |
information matrix The the from ratio. arises test | The test arises from the information matrix ratio. | 8,322 |
is and The corresponding derived normality is test proven. asymptotic its statistic | The corresponding test statistic is derived and its asymptotic normality is proven. | 8,323 |
process is of circulating mechanism the (CTCs). physical this of tumour biological dissemination cells Preceeding | Preceeding this biological mechanism is the physical process of dissemination of circulating tumour cells (CTCs). | 8,324 |
growth The than expected. normally was magnitude of around two-orders larger assumed rate | The assumed growth rate was around two-orders of magnitude larger than normally expected. | 8,325 |
is In lack of script, official there such Devnagari benchmark. | In Devnagari script, there is lack of such official benchmark. | 8,326 |
offline format The sample it memory. in occupies TIFF as stored images image are less | The offline sample images are stored in TIFF image format as it occupies less memory. | 8,327 |
data reduced. memory presented level further is binary Also, in so the requirement that is | Also, the data is presented in binary level so that memory requirement is further reduced. | 8,328 |
and Background: role vexing Understanding distinction the and function difficult. is between | Background: Understanding the distinction between function and role is vexing and difficult. | 8,329 |
them the test against Ontology Investigations practice (OBI). Biomedical I for in | I test them in practice against the Ontology for Biomedical Investigations (OBI). | 8,330 |
discuss in these and definitions Finally, I methods for applying an give practice. axiomatisation | Finally, I give an axiomatisation and discuss methods for applying these definitions in practice. | 8,331 |
are practice. paper current applicable, definitions formalizing Conclusions: this The in | Conclusions: The definitions in this paper are applicable, formalizing current practice. | 8,332 |
matrix nonnegative noisy algorithm for factorization present under a separability. We problems numerical (NMF) | We present a numerical algorithm for nonnegative matrix factorization (NMF) problems under noisy separability. | 8,333 |
to report experimental results. the Finally, apply document algorithm clustering, and the we | Finally, we apply the algorithm to document clustering, and report the experimental results. | 8,334 |
determine A understand challenge major to is molecular how biology in processes phenotypic features. | A major challenge in biology is to understand how molecular processes determine phenotypic features. | 8,335 |
We history . the mathematical induction review automation of the of | We review the history of the automation of mathematical induction . | 8,336 |
tasks Many inference large over exponentially probabilistic summations sets. involve | Many probabilistic inference tasks involve summations over exponentially large sets. | 8,337 |
is Compressed (CS-THz) imaging Sensing imaging a based technique. Terahertz computational | Compressed Sensing based Terahertz imaging (CS-THz) is a computational imaging technique. | 8,338 |
under CS state-of-the-art conducted systematic CS-THz scan algorithms the architecture. evaluation based We of | We conducted systematic evaluation of state-of-the-art CS algorithms under the scan based CS-THz architecture. | 8,339 |
We this a approach tackling problem. principled therefore propose for | We therefore propose a principled approach for tackling this problem. | 8,340 |
this for a propose approximately optimization greedy problem. dynamic, intractable solving We algorithm | We propose a dynamic, greedy algorithm for approximately solving this intractable optimization problem. | 8,341 |
Bayesian estimating the model white from matter propose atlas HYDIs. for a then We | We then propose a Bayesian model for estimating the white matter atlas from HYDIs. | 8,342 |
We work al. in Hosseinbor the adopt et given | We adopt the work given in Hosseinbor et al. | 8,343 |
stochastic volatility a and apply specifications. We range the method univariate of for bivariate | We apply the method for a range of univariate and bivariate stochastic volatility specifications. | 8,344 |
find networks. for optimal Bayesian to provably guarantee networks learning algorithms Exact | Exact algorithms for learning Bayesian networks guarantee to find provably optimal networks. | 8,345 |
may in limited due fail difficult or they to time However, tasks memory. learning | However, they may fail in difficult learning tasks due to limited time or memory. | 8,346 |
to heuristic research algorithms we networks. Bayesian anytime learn search-based adapt this several In | In this research we adapt several anytime heuristic search-based algorithms to learn Bayesian networks. | 8,347 |
fair optimization Multiobjective Decision Markov This (MOMDPs). in paper devoted Processes to is | This paper is devoted to fair optimization in Multiobjective Markov Decision Processes (MOMDPs). | 8,348 |
policies In setting, this study to of tradeoffs. we determination Lorenz-non-dominated the leading | In this setting, we study the determination of policies leading to Lorenz-non-dominated tradeoffs. | 8,349 |
of subsets polynomial-sized are approximations those The solutions. | The approximations are polynomial-sized subsets of those solutions. | 8,350 |
learning. approach Our information-driven intrinsic task-dependent support to task-independent, use motivation(s) is to | Our approach is to use task-independent, information-driven intrinsic motivation(s) to support task-dependent learning. | 8,351 |
examine protein in Drosophila pattern the embryo, Here Bicoid reproducible we the gradient. the earliest | Here we examine the earliest reproducible pattern in the Drosophila embryo, the Bicoid protein gradient. | 8,352 |
We consider the from causal distribution. directed graphs of learning joint an observational problem acyclic | We consider the problem of learning causal directed acyclic graphs from an observational joint distribution. | 8,353 |
correct an is prove evaluation. empirical the We RESIT and population provide setting in that | We prove that RESIT is correct in the population setting and provide an empirical evaluation. | 8,354 |
goalkeeping and job. a an (GK) is soccer is expert professional Goalkeeper complete in | Goalkeeper (GK) is an expert in soccer and goalkeeping is a complete professional job. | 8,355 |
seems without reliable In a success impossible achieving fact, GK. | In fact, achieving success seems impossible without a reliable GK. | 8,356 |
than dominant is effect successes other failures more and in players. His | His effect in successes and failures is more dominant than other players. | 8,357 |
game are mistakes those goalkeeper's. of a visible in The most | The most visible mistakes in a game are those of goalkeeper's. | 8,358 |
goalkeepers' done find soccer. the researches indexes Previously in used to are | Previously done researches are used to find the goalkeepers' indexes in soccer. | 8,359 |
some qualifications. have Soccer have experts a GK should found successful that | Soccer experts have found that a successful GK should have some qualifications. | 8,360 |
Here consider such class stratified models. we termed an models, of as additional graphical | Here we consider an additional class of such models, termed as stratified graphical models. | 8,361 |
Models Random discusses Utility {General (GRUMs)}. paper This | This paper discusses {General Random Utility Models (GRUMs)}. | 8,362 |
for algorithm general MAP a couple with GRUMs. inference this (MC-EM) Monte-Carlo-Expectation-Maximization We under based | We couple this with a general Monte-Carlo-Expectation-Maximization (MC-EM) based algorithm for MAP inference under GRUMs. | 8,363 |
for of also functions of the prove GRUMs. likelihood a We uni-modality class | We also prove uni-modality of the likelihood functions for a class of GRUMs. | 8,364 |
statistical emulating computationally are Gaussian expensive surrogates popular models for (GP) computer simulators. Process used | Gaussian Process (GP) models are popular statistical surrogates used for emulating computationally expensive computer simulators. | 8,365 |
the methods optimizing Previous function likelihood (e.g. for | Previous methods for optimizing the likelihood function (e.g. | 8,366 |
package, method GPMfit. proposed Matlab implemented a is The in | The proposed method is implemented in a Matlab package, GPMfit. | 8,367 |
based on characterized in We regulatory their studies kinetic relationships hormones. different nine | We characterized their regulatory relationships in nine kinetic studies based on different hormones. | 8,368 |
in main two that network the in identified We guard hubs cells. transport nitrate | We identified two main hubs in the network that transport nitrate in guard cells. | 8,369 |
transport a that is This sunflower nitrate physiological drought. of suggests critical response aspect to | This suggests that nitrate transport is a critical aspect of sunflower physiological response to drought. | 8,370 |
on inferences concept computational complexity irrelevance/independence adopted. the such The on of models depends | The computational complexity of inferences on such models depends on the irrelevance/independence concept adopted. | 8,371 |
independence inferences are trees ternary that show under We even strong in NP-hard variables. with | We show that inferences under strong independence are NP-hard even in trees with ternary variables. | 8,372 |
a text its problem. challenging value, images research general remains in Despite identifying however, | Despite its value, however, identifying general text in images remains a challenging research problem. | 8,373 |
on benchmark proposed The datasets. a detection detector state-of-the-art text methods outperforms scene few text | The proposed text detector outperforms state-of-the-art methods on a few benchmark scene text detection datasets. | 8,374 |
probability distributions provide for language over compact preference orderings. a representing PCP-nets | PCP-nets provide a compact language for representing probability distributions over preference orderings. | 8,375 |
are We useful that modelling argue noisy they aggregating preferences preferences. for or | We argue that they are useful for aggregating preferences or modelling noisy preferences. | 8,376 |
Graphical Potentials received Order considerable have interest with High recent (HOPs) years. models in | Graphical models with High Order Potentials (HOPs) have received considerable interest in recent years. | 8,377 |
of learning discrete the networks complete problem We Bayesian (BNs) consider from data. | We consider the problem of learning Bayesian networks (BNs) from complete discrete data. | 8,378 |
of as discrete (IP). an is integer problem formulated This program optimisation | This problem of discrete optimisation is formulated as an integer program (IP). | 8,379 |
the we of this allow have describe to IP. We steps efficient solving various taken | We describe the various steps we have taken to allow efficient solving of this IP. | 8,380 |
These sometimes earlier over results. show dramatic, improvements, | These show improvements, sometimes dramatic, over earlier results. | 8,381 |
bias-variance interesting introduce algorithms our that show several new We trade-offs. | We show that our new algorithms introduce several interesting bias-variance trade-offs. | 8,382 |
both the for (feedback directed latent procedure allows of and cycles variables. presence loops) The | The procedure allows for both directed cycles (feedback loops) and the presence of latent variables. | 8,383 |
the effect how and algorithm of assumptions the Simulations scales. illustrate discovery present these on | Simulations illustrate the effect of these assumptions on discovery and how the present algorithm scales. | 8,384 |
Bayesian networks. learns PC oriented maximally The algorithm causal | The PC algorithm learns maximally oriented causal Bayesian networks. | 8,385 |
(RCD) that causal algorithm discovery relational causal learns We relational present models. the | We present the relational causal discovery (RCD) algorithm that learns causal relational models. | 8,386 |
is applications. of pivotal Reliable importance tracking surveillance in | Reliable tracking is of pivotal importance in surveillance applications. | 8,387 |
is allow cases not z-identifiability to where first from generalize necessarily Z disjoint X. We | We first generalize z-identifiability to allow cases where Z is not necessarily disjoint from X. | 8,388 |
for complete also z-transportability. that show do-calculus is Our results | Our results also show that do-calculus is complete for z-transportability. | 8,389 |
we from CRAN available R implement package an have freely MPBART, To mpbart repositories. developed | To implement MPBART, we have developed an R package mpbart available freely from CRAN repositories. | 8,390 |
Browser enhancer as Genome developmental UCSC freely predictions be a Our genome-wide will available track. | Our genome-wide developmental enhancer predictions will be freely available as a UCSC Genome Browser track. | 8,391 |
effect is the change immediate rivers. The of lakes size and of | The immediate effect is the change of size of lakes and rivers. | 8,392 |
happen ignored. may their are Misclassification contents since color | Misclassification may happen since their color contents are ignored. | 8,393 |
implemented. colored achieve kinds of different this To and purpose, are descriptors SIFT introduced | To achieve this purpose, different kinds of colored SIFT descriptors are introduced and implemented. | 8,394 |
several The are real benchmarks. on out experiments carried | The real experiments are carried out on several benchmarks. | 8,395 |
in patterns embedded stochastic capture The proposes data. modeling second part to the the better | The second part proposes stochastic modeling to better capture the patterns embedded in the data. | 8,396 |
However, laws for systems structure. fail complex these network with | However, these laws fail for systems with complex network structure. | 8,397 |
in Here show cases that superellipses. the these are we eigenvalues by described | Here we show that in these cases the eigenvalues are described by superellipses. | 8,398 |
complex develop also a We dominant of method eigenvalue the estimate new networks. to analytically | We also develop a new method to analytically estimate the dominant eigenvalue of complex networks. | 8,399 |
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