ライフサイエンスコーパス: partial differential equation

1 characteristic directions of the underlying partial differential equation.

2 the solution of a discretized version of the partial differential equation.

3 sified in mathematics as a linear, parabolic partial-differential equation.

4 e modeled the dynamics of T cell density via partial differential equations.

5 to learn Green's functions of hidden linear partial differential equations.

6 earn effective evolution laws in the form of partial differential equations.

7 ele across a landscape using two-dimensional partial differential equations.

8 ITE as a quantum numerical solver for linear partial differential equations.

9 -likelihood analysis in problems governed by partial differential equations.

10 uous spatiotemporal dynamical evolution from partial differential equations.

11 ochastic cellular automata and deterministic partial differential equations.

12 lvers of full order models (FOM) for solving partial differential equations.

13 s of TCRs into estimated model parameters of partial differential equations.

14 The model is represented by a system of partial differential equations.

15 l is a coupled two-phase two-layer system of partial differential equations.

16 ls is often modeled using reaction-diffusion partial differential equations.

17 the dynamics of root apical meristems, using Partial Differential Equations.

18 ent heat, and I ended up numerically solving partial differential equations.

19 , enables the discretization and solution of partial differential equations.

20 odel based on a system of reaction-diffusion partial differential equations.

21 rlying ACTIS can be described by a system of partial differential equations allowing for a virtual AC

22 tal region are predicted by solving a set of partial differential equations (Ampere's law and Gauss'

23 We then solve these partial differential equations and compare them to the s

24 cs of the combined system can be mapped to a partial differential equation, and for a suitable choice

25 n is very different from the solution of the partial differential equation, and so the ordinary diffe

26 y for the group selection model by solving a partial differential equation, and that it is mathematic

27 inflammatory mediators is described through partial differential equations, and immune cells (neutro

28 problems of ordinary differential equations, partial differential equations, and mean-field control p

29 Recently, fractional- order partial differential equations are attracting attention

30 Although partial differential equations are available to describe

31 tions, wherein the unknown parameters of the partial differential equations are initially assigned ra

32 h a mechanical model, we show that the model partial differential equations are similar in form.

33 Discontinuities in the solutions of these partial differential equations are widely recognized as

34 In this article, we show that the partial differential equations arising from classical el

35 h as molecular dynamics (MD), and stochastic partial differential equation-based hydrodynamic models,

36 es from additional nonlinear, time-dependent partial differential equations (Burgers equation, Kuramo

37 lly similar to those previously derived from partial differential equations, but there are also some

38 al method, instead of solving the equivalent partial differential equation by a discretization method

39 A set of first order, partial differential equations comprise the model and we

40 from observing thermal wave dynamics, using partial differential equation-constrained optimization.

41 d valley networks is produced by a system of partial differential equations coupling landscape evolut

42 Parameters derived from partial differential equation describing the process of

43 that there exists an analytical solution of partial differential equations describing mass transfer

44 The model consists of a system of nonlinear partial differential equations describing the interactio

45 The model takes the form of partial differential equations describing the membrane c

46 may then be simulated using either the VCell partial differential equations deterministic solvers or

47 of their model using a displacement integro-partial differential equation (DiPDE) population density

48 They rely on an initial value partial differential equation for a propagating level se

49 ted cytoplasmic compartment is replaced by a partial differential equation for the buffered diffusion

50 The model has three components: a transient partial differential equation for the simultaneous diffu

51 We consider a set of partial differential equations for diffusion and reactio

52 rrent pulses is preserved by the full set of partial differential equations for electrodiffusion.

53 membrane potential dynamics, and a system of partial differential equations for myoplasmic and lumena

54 atical framework based on reaction-diffusion partial differential equations for studying the dynamics

55 tion, we consider a spatio-temporal model of partial differential equations for the NF-kappaB pathway

56 The model consists of a nonlinear system of partial differential equations for the telomere classes.

57 with sparse regression to discover governing partial differential equations from scarce and noisy dat

58 n one or two dimensions via a set of coupled partial differential equations) generalize to a physical

59 odel in the framework of a nonlinear integro-partial differential equation governing biofluids flow i

60 alytic solutions for a system of n+1 coupled partial differential equations governing biomolecular ma

61 rkin family of methods for solving continuum partial differential equations has shown promise in real

62 the orthogonal dynamics equation which is a partial differential equation in a high dimensional spac

63 ynamics in physical applications governed by partial differential equations in real-time is nearly im

64 fy conservation laws, which are expressed as partial differential equations in space and time.

65 The model consists of a coupled system of partial differential equations in the partially healed r

66 ng difficulties in the analysis of nonlinear partial differential equations including elliptic-hyperb

67 Nested Laplace Approximation with Stochastic Partial Differential Equation, INLA-SPDE) is used to pre

68 The model, based on age-structured partial differential equations, integrates experimental

69 similarity variables to simplify the complex partial differential equations into ordinary differentia

70 into the basic set of equations, a nonlinear partial differential equation is derived to describe the

71 ity transformation, the nonlinear systems of partial differential equations is converted into nonline

72 A system of nonlinear transient partial differential equations is solved numerically usi

73 in mathematical fluid dynamics and nonlinear partial differential equations is to determine whether s

74 al model representing mycelia as a system of partial differential equations is used to simulate comba

75 he second model, posed as a set of nonlinear partial differential equations, is a continuous treatmen

76 alysis, as well as the numerical solution of partial differential equations, is required to carry out

77 ases can only be described by such a complex partial differential equation model and not by ordinary

78 The unknown functions in this nonlinear partial differential equation model are determined using

79 A density-based partial differential equation model describes the disper

80 A coupled partial differential equation model for MPB dispersal an

81 We formulate a simple partial differential equation model in an effort to qual

82 A partial differential equation model is developed to unde

83 In this article, we construct a partial differential equation model of a single colonic

84 We present a hybrid cellular automata-partial differential equation model of moderate complexi

85 d on these experimental data, we developed a partial differential equation model of MYOF effects on c

86 In this paper, we present a partial differential equation model that accounts for th

87 hat tracks the position of individuals and a partial differential equation model that describes locus

88 We used a partial differential equation model that postulates thre

89 We formulated a minimal one-dimensional partial differential equation model that reproduced the

90 We employ an age-structured partial differential equation model to characterize seas

91 nd strict adherence to the Fisher-Kolmogorov partial differential equation model, which is adapted fo

92 x software for mixed-effects modeling with a partial differential equation model.

93 We first derived a partial differential equations model of gas exchange on

94 Fitting a partial differential equations model of population dynam

95 In this article, we formulate a partial-differential-equation model to describe the inte

96 uations and extracellular reaction-diffusion partial differential equations, model gene regulation.

97 tal results, is shown by reaction-diffusion, partial differential equation modeling and simulation to

98 By implementing experimental in vitro data, partial differential equation modeling, as well as autom

99 into one- and two-dimensional inhomogeneous partial differential equation models of atrial tissue.

100 odel corresponds probabilistically to common partial differential equation models of resistance allow

101 Previous partial differential equation models of tree water flow

102 Using partial differential equation models, new information ca

103 that captures intracellular dynamics through partial differential equation models.

104 thematical tools for investigating nonlinear partial differential equation (NLPDEs) and provide new i

105 sing problem appear in the form of nonlinear partial differential equations (NPDEs) against the conse

106 such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs).

107 A continuum mechanical model and associated partial differential equations of the GC model have rema

108 n (FPE) (in this case an advection-diffusion partial differential equation on a growing domain) which

109 takes the mathematical form of three coupled partial differential equations, one that describes the m

110 ds based on ordinary differential equations, partial differential equations, or the Gillespie stochas

111 The optimization subjects to a set of partial differential equation (PDE) constraints that des

112 -fidelity dynamical models directly in their partial differential equation (PDE) forms with both Mark

113 We also applied the reaction-diffusion partial differential equation (PDE) mathematical model,

114 derived from a mechanistic, spatiotemporal, Partial Differential Equation (PDE) model of epidemic sp

115 Reaction-diffusion partial differential equation (PDE) models have been onl

116 mputational modeling can then be used to fit partial differential equation (PDE) models to the data,

117 Thus, it outperforms traditional partial differential equation (PDE) solvers, machine lea

118 n Hamiltonians, which allows us to solve any partial differential equation (PDE) that is equivalent t

119 The solution to the diffusion partial differential equation (PDE) that mimics the evol

120 plex dynamics from time series of images and Partial Differential Equation (PDE) trajectories.

121 l (3D) segmentation process with an unsteady partial differential equation (PDE), which allows accele

122 onsistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimiza

123 spatial model converges to the solution of a partial differential equation (PDE).

124 zed form of the governing reaction-diffusion partial differential equation (PDE).

125 Partial differential equations (PDE) learning is an emer

126 Partial differential equations (PDE) were built to model

127 t laboratory experiments or macroscale-level partial differential equations (PDEs) (among others).

128 in modelling physical processes described by partial differential equations (PDEs) and are in princip

129 The partial differential equations (PDEs) are derived using

130 Evolutionary, pattern forming partial differential equations (PDEs) are often derived

131 ing potential for the recovery of underlying partial differential equations (PDEs) from continuum sim

132 Data-driven discovery of partial differential equations (PDEs) is a promising app

133 The numerical solution of partial differential equations (PDEs) is challenging bec

134 Solving partial differential equations (PDEs) is the cornerstone

135 Partial differential equations (PDEs) play a central rol

136 are typically complex and involve dozens of partial differential equations (PDEs) representing vario

137 have recently become attractive for solving partial differential equations (PDEs) that describe phys

138 We use a framework, based on partial differential equations (PDEs) to explore how res

139 We argue that partial differential equations (PDEs), beyond convention

140 uations of a physical system, represented by partial differential equations (PDEs), from data is a ce

141 oral systems, whose dynamics are governed by partial differential equations (PDEs), state estimators

142 g the material transport process via solving partial differential equations (PDEs), they require long

143 del agents and diffusive fields described by partial differential equations (PDEs).

144 f scientific computing's arsenal for solving partial differential equations (PDEs).

145 racteristics and assumptions is framed using partial differential equations (PDEs).

146 lated Raman scattering into a unified set of partial differential equations persists.

147 This model couples macroscale partial differential equations posed over the tissue to

148 Computational models using partial differential equations provide mechanistic insig

149 ng experimental measurements and chemotactic Partial Differential Equations requires knowledge of the

150 Although the Lamm partial differential equation rigorously predicts the ev

151 rough numerical simulations of the governing partial differential equations, showing that concentrati

152 and bifurcation structure of this system of partial-differential equations, showing the existence of

153 ge can be applied to traditional ordinary or partial differential equation simulations as well as age

154 integrating capabilities of a deterministic partial differential equation solver with a popular part

155 In many stochastic partial differential equations (SPDEs) involving random

156 ffects of electric fields on cells have used partial differential equations such as Laplace's equatio

157 difference discrete approximations to an sxs partial differential equation system with suitable obser

158 d computational model (agent-based model and partial differential equation system), we developed a si

159 experimentally, on discovering a variety of partial differential equation systems with different lev

160 differential equations to a single nonlinear partial differential equation that is solved numerically

161 NLSE) stands out as the dispersive nonlinear partial differential equation that plays a prominent rol

162 In this study, we write down the partial differential equations that allow for spatial as

163 mputationally demanding time stepping of the partial differential equations that are often used to mo

164 ction kinetic models (in the form of coupled partial differential equations) that assume filament ine

165 For Partial Differential Equations, the crossing of infinity

166 existing numerical solutions of the relevant partial differential equations, the effective particle m

167 meter is also assigned to a fractional-order partial differential equation to depict the previous pow

168 oretical model that starts from a well-known partial differential equation to describe the dithering

169 Here we examine the ability of each class of partial differential equation to support travelling wave

170 e our results to those based on ordinary and partial differential equations to better understand how

171 l modelling approaches, we derive systems of partial differential equations to capture the evolution

172 This model uses partial differential equations to describe the binding i

173 We used partial differential equations to explore the potential

174 mics, using nested birth-death processes and partial differential equations to model natural selectio

175 We have used partial differential equations to model the flow of spat

176 es, we then show how one can learn effective partial differential equations, using neural networks, t

177 By incorporating this relation in a partial differential equation, we demonstrate that this

178 loiting the explicitly spatial nature of the partial differential equations, we are also able to mani

179 We avoid the use of partial differential equations which typically appear in

180 rocess gives rise to 22 different classes of partial differential equation, which can include Allee k

181 how well the method works to solve nonlinear partial differential equations, which are common in math

182 First, constant coefficient partial differential equations, which are randomly force

183 The model consists of a system of nonlinear partial differential equations whose parameters reflect