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a of of We few the review evolution. of models the genealogies properties statistical
We review the statistical properties of the genealogies of a few models of evolution.
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these way of times are simple introducing how discuss We in modified selection. a
We discuss how these times are modified in a simple way of introducing selection.
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differentiated slow found processes. We the from emerge indeed the promoter states binding/unbinding can
We found indeed the differentiated states can emerge from the slow promoter binding/unbinding processes.
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slow multiple we promoter Furthermore, found meta-stable under binding/unbinding, states. differentiated
Furthermore, under slow promoter binding/unbinding, we found multiple meta-stable differentiated states.
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can the explain of in experiments. origin the multiple recent observed This states
This can explain the origin of multiple states observed in the recent experiments.
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In kinetic and quantify addition, the reprogramming. we differentiation pathways for
In addition, we quantify kinetic pathways for the differentiation and reprogramming.
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This dynamics in cells. stem multipotent progenitor the non-equilibrium captures or
This captures the non-equilibrium dynamics in multipotent stem or progenitor cells.
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motif that suggest noisy we flow information a in maximizes network. Here, this
Here, we suggest that this motif maximizes information flow in a noisy network.
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at In TFs, of case up-stream latter cross-regulation. the criterion hints the
In the case of TFs, the latter criterion hints at up-stream cross-regulation.
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nodes. consider We two with of types networks
We consider networks with two types of nodes.
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networks, central- in possesses fundamental widespread properties. two architecture, ized gene This
This central- ized architecture, widespread in gene networks, possesses two fundamental properties.
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perturbations system. respect random the this with is organization Moreover, to of robust
Moreover, this organization is robust with respect to random perturbations of the system.
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be edge accurate. These assume techniques image to the
These techniques assume the edge image to be accurate.
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perceptually based presents techniques the This fusion important Wavelet features. Discrete combining for paper image
This paper presents the Discrete Wavelet based fusion techniques for combining perceptually important image features.
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modifications the SPIHT This on some presents algorithm. paper
This paper presents some modifications on the SPIHT algorithm.
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object ray-casting inner feature are on estimation based point. Existing projection from techniques the
Existing object projection feature estimation techniques are based on ray-casting from the inner point.
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develop In this these numerical we approximations for quantities. paper,
In this paper, we develop numerical approximations for these quantities.
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approximation sparse for We describe coding. method of a fast
We describe a method for fast approximation of sparse coding.
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averaging cascades and transform operators. with convolutions It modulus non-linear wavelet
It cascades wavelet transform convolutions with non-linear modulus and averaging operators.
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is heuristics inadequate. infrastructure existing However, often for search defining
However, existing infrastructure for defining search heuristics is often inadequate.
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remain unexplored. a performance may As major result, in improvements
As a result, major improvements in performance may remain unexplored.
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from spatially a technique low-resolution observed SR is image to high-resolution images. a multiple estimate
SR is a technique to estimate a spatially high-resolution image from observed multiple low-resolution images.
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preserves natural compound images model edges. A provides Gaussian preferable for MRF that prior a
A compound Gaussian MRF model provides a preferable prior for natural images that preserves edges.
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(PSNR). for objective the estimator ratio the is signal-to-noise peak function of optimal PM
PM is the optimal estimator for the objective function of peak signal-to-noise ratio (PSNR).
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variational determined estimator is (VB). numerically using This by Bayes
This estimator is numerically determined by using variational Bayes (VB).
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methods. method existing the experiments, In roughly overcomes proposed
In experiments, the proposed method roughly overcomes existing methods.
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technique. of the with showing provide the experiments performance good real We images
We provide experiments with real images showing the good performance of the technique.
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This been discrimination has used as tasks image framework for such classification. also
This framework has also been used for discrimination tasks such as image classification.
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exploit problem. algorithm online derived an we the Then, to solve
Then, we exploit an online algorithm to solve the derived problem.
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be In to set credal is particular, neither convex closed. nor assumed the
In particular, the credal set is assumed to be neither convex nor closed.
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test against our it to As model, biological applications of we observations. more applied further
As further applications of our model, we applied it to test against more biological observations.
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partitioning describe such this approach new data. paper high-dimensional we a for In
In this paper we describe a new approach for partitioning such high-dimensional data.
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processing done is using simulation MATLAB complete The image model.
The complete image processing is done using MATLAB simulation model.
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law. is transformation Morphological as Finally, follows Weber's organized and as paper this
Finally, this paper is organized as follows as Morphological transformation and Weber's law.
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quite are lower expensive. that radiation Systems risk generally have
Systems that have lower radiation risk are generally quite expensive.
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pedicle position orientation the screw fixation. drill and of clinically important is very The in
The position and orientation of the drill is clinically very important in pedicle screw fixation.
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of fragments of a we a bacteria consider set. mixture certain this In research, genome
In this research, we consider a mixture of genome fragments of a certain bacteria set.
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material are the Fields by capturing real-world properties The defined Reflectance objects. the of
The material properties are defined by capturing the Reflectance Fields of the real-world objects.
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fusion for of Shenoy's algorithm discrete algorithm influence is The diagrams. an solution extension
The solution algorithm is an extension of Shenoy's fusion algorithm for discrete influence diagrams.
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and solving framework examples. two are The algorithm small illustrated by
The algorithm and framework are illustrated by solving two small examples.
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possibilistic knowledge is of a result often in which a formulas. set weighted base They
They often result in a possibilistic knowledge base which is a set of weighted formulas.
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logic Although the inconsistency suers from possibilistic well-known is "drowning tolerant, it effect".
Although possibilistic logic is inconsistency tolerant, it suers from the well-known "drowning effect".
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These of change principle capture postulates minimal some the sense. in
These postulates capture the principle of minimal change in some sense.
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of logic MAP introduces parameterization networks. Markov paper inference a inference, The k-bounded in MAP
The paper introduces k-bounded MAP inference, a parameterization of MAP inference in Markov logic networks.
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by are aids improve Rollating popular walkers to mobility used older control. balance adults
Rollating walkers are popular mobility aids used by older adults to improve balance control.
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and walker techniques recognize design compare activities. to We several related
We design and compare several techniques to recognize walker related activities.
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presented. comprehensive retirement evaluation community and walker a is users subjects from with A control
A comprehensive evaluation with control subjects and walker users from a retirement community is presented.
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define sets answer then generalized PASP to characterization programs. is of This naturally
This characterization is then naturally generalized to define answer sets of PASP programs.
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which particular world represents classes. everything real object In an is
In real world everything is an object which represents particular classes.
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Every described can be its object by fully attributes.
Every object can be fully described by its attributes.
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attributes of objects. real dataset number contains and Any world large
Any real world dataset contains large number of attributes and objects.
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result of shows efficiency the proposed The the method.
The result shows the efficiency of the proposed method.
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BLOG, for well-known language. been a has OUPM It implemented
It has been implemented for BLOG, a well-known OUPM language.
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combinator that has prove several We this properties. good
We prove that this combinator has several good properties.
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sequential framework Decentralized expressive multi-agent an for provide decision POMDPs making.
Decentralized POMDPs provide an expressive framework for multi-agent sequential decision making.
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that solvers. compares on Experiments domains EM benchmark show the against favorably state-of-the-art
Experiments on benchmark domains show that EM compares favorably against the state-of-the-art solvers.
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equidistantly nodes on and the the image. algorithms distribute However, uniformly graph's graph-based
However, graph-based algorithms distribute the graph's nodes uniformly and equidistantly on the image.
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is a term added to cut Then, to prefer smoothness shape. a the force particular
Then, a smoothness term is added to force the cut to prefer a particular shape.
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of are the when indistinguishable This can areas background. from object be the useful, strategy
This strategy can be useful, when areas of the object are indistinguishable from the background.
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a as consciousness by defined of propose data. relations We theory partial typical
We propose a partial theory of consciousness as relations defined by typical data.
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both theoretically and experimentally. proposed can applied tested theory be The and
The proposed theory can be applied and tested both theoretically and experimentally.
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fully is typical using established discrete how Precisely mathematics. relations determines data
Precisely how typical data determines relations is fully established using discrete mathematics.
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the analytically. over filter, observations marginalize can EKF Since is the we first-order a
Since the EKF is a first-order filter, we can marginalize over the observations analytically.
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designed and that to an DecRSPI lack problems improve model. is explicit scalability tackle
DecRSPI is designed to improve scalability and tackle problems that lack an explicit model.
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Monte- a of uses Carlo to algorithm The sample states. reachable methods belief generate
The algorithm uses Monte- Carlo methods to generate a sample of reachable belief states.
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belief computes based it for state on a estimations. the rollout Then joint each policy
Then it computes a joint policy for each belief state based on the rollout estimations.
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A to policy us represent allows new representation solutions compactly.
A new policy representation allows us to represent solutions compactly.
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larger that existing intractable can for It problems algorithms. solve are planning
It can solve larger problems that are intractable for existing planning algorithms.
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effectiveness confirm and the of results scalability Experimental approach. the
Experimental results confirm the effectiveness and scalability of the approach.
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known as is This or block-modelling block-clustering.
This is known as block-modelling or block-clustering.
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integrated (SBM) The block parameters out. the blockmodel stochastic with model is
The model is the stochastic blockmodel (SBM) with block parameters integrated out.
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cluster The memberships. a clusters over the resulting number defines marginal distribution of posterior and
The resulting marginal distribution defines a posterior over the number of clusters and cluster memberships.
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allocation on The based sampler. the is algorithm
The algorithm is based on the allocation sampler.
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to compute them. it Our makes reformulation possible
Our reformulation makes it possible to compute them.
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how the procedure We done and is and this illustrate its results. show
We show how this is done and illustrate the procedure and its results.
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ways. unique is in Our two algorithm
Our algorithm is unique in two ways.
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with lifted the First, it variables efficiency improves substantially inference domains. of continuous of
First, it substantially improves the efficiency of lifted inference with variables of continuous domains.
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algorithm which way. Second, a it handles is the lifted exact first inference in RCMs
Second, it is the first exact inference algorithm which handles RCMs in a lifted way.
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econometrics. illustrated algorithm The example an over is from
The algorithm is illustrated over an example from econometrics.
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formulas. conventional dual variable-based Unlike in our logical realm algorithms algorithms, work of the
Unlike conventional variable-based algorithms, our algorithms work in the dual realm of logical formulas.
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reconstruction interesting of With cameras the amount optimal large strategy. determine to it a becomes
With a large amount of cameras it becomes interesting to determine the optimal reconstruction strategy.
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how different changes considering error cameras. reconstruction by the
how the reconstruction error changes by considering different cameras.
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work, In reconstruction derived. error is of the this approximation variance an first,
In this work, first, an approximation of the reconstruction error variance is derived.
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introduce The into System Air cockpit. will sensor Generation the Next technologies advanced Transportation new,
The Next Generation Air Transportation System will introduce new, advanced sensor technologies into the cockpit.
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call different pilot and alerting will hazards automation plans. Different states for
Different hazards and pilot states will call for different alerting automation plans.
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explores alternative using compilation This algorithms techniques. paper
This paper explores alternative algorithms using compilation techniques.
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adaptations compilation-based first propose of We methods. possibilistic probabilistic standard
We first propose possibilistic adaptations of standard compilation-based probabilistic methods.
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by results. is also result experimental This confirmed
This result is also confirmed by experimental results.
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quadratic present particular, a kernel. In we
In particular, we present a quadratic kernel.
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construction enumerative Inference based logic languages in these over is of programs. proofs on
Inference in these languages is based on enumerative construction of proofs over logic programs.
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Consequently, of languages permit with variables these distributions. random use continuous very limited
Consequently, these languages permit very limited use of random variables with continuous distributions.
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The generalizes learning Networks. Bayesian used for PRISM and algorithm the naturally ones Hybrid
The learning algorithm naturally generalizes the ones used for PRISM and Hybrid Bayesian Networks.
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strategy struggle to winning rapidly. coevolutionary One is a evolve for
One strategy for winning a coevolutionary struggle is to evolve rapidly.
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ecology. the Speciation of is the room" community in "elephant
Speciation is the "elephant in the room" of community ecology.
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ignored speciation often its dimension. Yet, is spatial of or completely stripped
Yet, speciation is often completely ignored or stripped of its spatial dimension.
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allowed to theory model have based effectively Recent on complex network approaches ecologists landscapes.
Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes.
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longer males. gave Females than estimates consistently
Females consistently gave longer estimates than males.
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had difference This to however mathematics. in in correlation do overall skills with nothing
This difference in correlation however had nothing to do with overall skills in mathematics.
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two latent We unknown blurring the a image with create by CBP kernels. same
We create a CBP by blurring the same latent image with two unknown kernels.
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bivariate two domain. kernels polynomials the coprime in are z when mapped The to
The two kernels are coprime when mapped to bivariate polynomials in the z domain.
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