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NA Digest, V. 20, # 45

NA Digest Tuesday, November 24, 2020 Volume 20 : Issue 45


Today's Editor:

Daniel M. Dunlavy
Sandia National Labs
dmdunla@sandia.gov

Today's Topics: Subscribe, unsubscribe, change address, or for na-digest archives: http://www.netlib.org/na-digest-html/faq.html

Submissions for NA Digest:

http://icl.utk.edu/na-digest/


From: Edmond Chow echow@cc.gatech.edu
Date: November 22, 2020
Subject: H2Pack Software for Kernel Matrices


H2Pack is a library that provides linear-scaling storage and
linear-scaling matrix-vector multiplication for dense kernel matrices.
This is accomplished by storing the kernel matrices in the H2
hierarchical block low-rank representation. It can be used for
Gaussian processes, solving integral equations, Brownian dynamics, and
other applications.

The main strength of H2Pack is its ability to efficiently construct H2
matrices in linear time for kernel functions used in Gaussian
processes (up to 3-D data) by using a new proxy point method. Kernel
functions from computational physics, e.g., Coulomb, Stokes, can also
be used. H2Pack is optimized for shared-memory multicore
architectures, including the use of vectorization for evaluating
kernel functions. H2Pack provides C/C++ and Python interfaces.

Software released with open-source MIT license:
https://github.com/scalable-matrix/H2Pack


From: Mathias J Krause mathias.krause@kit.edu
Date: November 19, 2020
Subject: OpenLB release 1.4 available for download


The developer team is very happy to announce the release of the next
version of OpenLB. The updated open-source Lattice Boltzmann (LB) code
is now available for download at the project website www.openlb.net

The changes and new features are:
1 Enhanced user experience for interfaces
2 Additional multiphysics models
3 Performance improvements in some workloads
4 New examples
5 Minor improvements and developer notes

Compatibility tested on
- OSX: macOS 10.13.6: Clang 10 (1000.10.44.4)
- Linux: Intel 18, 19, 19.1; GCC 7.5, 8.2.1, 9.3, 10.2; Clang 7
- Windows 10: Debian WSL: GCC 7.5, 8.2.1, 9.3;
- Intel MPI 2019 Update 5, OpenMPI 2.1.1 and higher

PS: Please consider joining the developer team by contributing your
code. Together we can strengthen the LB community by sharing our
research in an open and reproducible way! Feel free to contact us
here: "Contact-Button"



From: Suzanne Shontz shontz@ku.edu
Date: November 20, 2020
Subject: Call for papers, PDSEC Workshop, May 2021


The 22nd IEEE International Workshop on Parallel and Distributed
Scientific and Engineering Computing (PDSEC-21) (http://www.ieee-
tcsc.org/2021/pdsec/) will be held on May 21, 2021 in Portland, Oregon
in conjunction with IPDPS 2021. Given the pandemic, the conference
organizers are planning for different potential scenarios, including a
fully virtual conference.

Deadline: PDSEC-21 deadline: 22 Jan 2021 (AoE)

The technological trends in HPC system evolution indicates an
increasing burden placed on application developers due to the
management of the unprecedented complexity levels of hardware and its
associated performance characteristics. Many existing scientific
applications codes are unlikely to perform well on future systems
without major modifications or even complete rewrites. In the future,
it will be necessary to utilize, in concert, many characteristics such
as multiple levels of parallelism, many lightweight cores, complex
memory hierarchies, novel I/O technology, power capping, system-wide
temporal/spatial performance heterogeneity and reliability concerns.
The parallel and distributed computing (PDC) community has developed
new programming models, algorithms, libraries and tools to meet these
challenges in order to accommodate productive code development and
effective system use. However, the scientific application community
still needs to identify the benefit through practical evaluations.
Thus, the focus of this workshop is on methodologies and experiences
used in scientific and engineering applications and algorithms to
achieve sustainable code development for better productivity,
application performance and reliability.


From: Richard Laugesen laugesen@illinois.edu
Date: November 19, 2020
Subject: Internship Project Developer Position, Univ of Illinois


Do you thrive on new challenges and taking responsibility in a
collaborative environment? Do you take a strategic approach to your
work?

The University of Illinois at Urbana-Champaign, Department of
Mathematics seeks applicants for the position of Visiting Internship
Project Developer with Inmas (https://inmas.us), a new program funded
by the NSF, with twin hubs at the University of Illinois and Johns
Hopkins University.

The Internship Network in the Mathematical Sciences (Inmas) will aid
industry, government and non-profit partners in solving strategic
challenges by developing internship projects that transform graduate
students' career readiness and strengthen the nation's innovation
ecosystem.

Your role will be to establish a network of companies and government
hosts in Illinois and neighboring states, to recognize project
opportunities at these organizations where the mathematical sciences
can make a positive impact, and to work with Inmas partner
universities to match their talented and enthusiastic students with
the Inmas-funded internship positions. Location: Champaign-Urbana,
Illinois. Crucial skills: a PhD in Mathematics, Applied Mathematics,
Statistics, or a closely related field, curiosity about the world, and
a willingness to learn.

This is a full-time, benefits eligible, visiting academic professional
position appointed on a 12-month service basis. Deadline to apply is
December 15, 2020. The expected start date is as soon as possible
after the closing date. The position will run for up to 2.5 years, and
longer if the grant is extended. For complete details visit
https://jobs.illinois.edu.



From: Greg Fasshauer fasshauer@mines.edu
Date: November 19, 2020
Subject: Faculty Positions, Colorado School of Mines


Colorado School of Mines will be hiring 12 new faculty members for the
coming year, in 3 cluster areas: Computational Science and Data
Analytics, Advanced Manufacturing & Materials, and Quantum Information
& Electronic Materials and Devices. Candidates from many backgrounds
will be considered in these areas, and ultimately hired into the
best-fit department for them. Mines is especially interested in
qualified candidates who can contribute to the diversity and
excellence of the academic community. Please send any qualified
candidates our way - there is a wide range of potential fit for
Applied Mathematicians, Statisticians, Computational Scientists, and
Data Scientists!

- Computational Science and Data Analytics Faculty Positions
- Advanced Manufacturing and Materials Faculty Positions
- Quantum Information, Electronic Materials and Devices Faculty
Positions

Apply here: https://jobs.mines.edu/



From: Andras Balogh andras.balogh@utrgv.edu
Date: November 17, 2020
Subject: Faculty Positions, Univ of Texas Rio Grande Valley


The School of Mathematical and Statistical Sciences at the University
of Texas Rio Grande Valley has three tenure-track faculty
openings. For more information follow the links below.

- Computational Mathematics: https://careers.utrgv.edu/postings/26422
- Statistics/Computational Mathematics: https://careers.utrgv.edu/postings/=
26423
- Mathematics Education: https://careers.utrgv.edu/postings/26424


From: Bengt Fornberg fornberg@colorado.edu
Date: November 20, 2020
Subject: Tenure Track Position, Computational Math, UC Boulder


The Department of Applied Mathematics at the University of Colorado
Boulder (CU Boulder) encourages applications for a tenure track
faculty position at the Assistant Professor level to begin August
2021. We are looking for candidates in the area of computational
mathematics, with possible areas of emphasis including numerical
analysis of differential equations, randomized numerical linear
algebra, optimization and inverse problems, scientific computing, and
related areas.

This position requires a commitment to supporting the diverse student
populations in our department and its associated campus educational
mission, a dedication to teaching in our undergraduate and graduate
programs, and developing and conducting an innovative independent
research program. The department firmly believes that the
effectiveness and creativity of a group is strengthened by
contributions from a broad range of perspectives. As such, we
particularly welcome candidates from groups that are historically
underrepresented in our field and/or candidates that have demonstrated
leadership toward building an equitable and inclusive scholarly
environment.

The University of Colorado Boulder is committed to building a
culturally diverse community of faculty, staff, and students dedicated
to contributing to an inclusive campus environment. We are an Equal
Opportunity employer, including veterans and individuals with
disabilities

For inquiries, please contact our department chair (and search
committee chair) Prof. Keith Julien, keith.julien@colorado.edu. For
details and to apply, see
https://jobs.colorado.edu/jobs/JobDetail/?jobId=3D27537. Applications
submitted by January 30, 2021 will receive full consideration.


From: Heike Sill heike.sill@wias-berlin.de
Date: November 18, 2020
Subject: Research Assistant Position, Image Processing, WIAS, Germany


WIAS invites applications for a Research Assistant Position (m/f/d)
(Ref. 20/26) in the Research Group "Stochastic Algorithms and
Nonparametric Statistics" (Head: Prof. Dr. Vladimir Spokoiny) starting
at January 1st, 2021.

The preconditions are a completed scientific university education as
well as a doctorate in the field of mathematics. Wanted: We are
seeking outstanding scientists in a research field in the field of
statistics or machine learning.

The research area comprises the following topics among other:
- Image processing
- statistical inverse problems

Very good English skills are still expected. International experience
is also advantageous.

Technical queries should be directed to Prof. Dr. V. Spokoiny
(Vladimir.Spokoiny@wias-berlin.de). The position is remunerated
according to TVoD and is limited to three years. The work schedule
is 39 hours per week, and the salary is according to the German TVoeD
scale.

Please, see here for more information: https://short.sg/j/8127927



From: Heike Sill heike.sill@wias-berlin.de
Date: November 24, 2020
Subject: Research Assistant Position, Optimization, WIAS, Germany


WIAS invites in the Research Group "Nonsmooth Variational Problems and
Operator Equations" (Head: Prof. Dr. M. Hintermuller) applications for
a Research Assistant Position (f/m/d) (Ref. 20/27). to be filled at
the earliest possible date. The position is associated with the
research project "Equilibria for Energy Markets with Transport" within
the Berlin Mathematics Research Center MATH+.

The purpose of the position is to carry out research in the field of
modeling, analytic, optimization and numerical aspects of generalized
Nash equilibrium problems with partial differential equation
constraints. The position offers the possibility to do a doctorate
(PhD).

Requirements: A completed university degree in mathematics or a
related discipline (preferably with very good results); Knowledge of
partial differential equations, continuous optimization and applied
functional analysis; Experience in the field of numerical and
computer-aided implementation; a high proficiency in spoken and
written English.

See here for more information: https://short.sg/j/8183817


From: Boyce Griffith boyceg@email.unc.edu
Date: November 20, 2020
Subject: Postdoc Position, Cardiovascular modeling, UNC-Chapel Hill


Applications are invited for a postdoctoral research associate in the
Cardiovascular Modeling and Simulation group at the University of
North Carolina at Chapel Hill, which is affiliated with the Carolina
Center for Interdisciplinary Applied Mathematics at UNC-Chapel Hill,
and the Computational Medicine Program and the McAllister Heart
Institute at UNC School of Medicine. Potential areas of research
include (but are not limited to) computational models of:

- cardiac fluid dynamics, especially therapies for valvular heart
disease such as transcatheter valve replacement/implantation;
- cardiac electro-mechanical coupling; and
- cardiac electrophysiology, especially atrial fibrillation.

Our group also actively develops computational methods and software to
enable such applications (e.g., https://ibamr.github.io), and funds
may be available to support a position that focuses primarily on
method development rather than applications.

A Ph.D. in Mathematics, Computer Science, Biomedical Engineering, or a
related field is required.

Applicants should also have substantial experience with scientific
computing using compiled software languages (e.g., C, C++, Fortran).

The University of North Carolina at Chapel Hill is an equal
opportunity and affirmative action employer. All qualified applicants
will receive consideration for employment without regard to age,
color, disability, gender, gender expression, gender identity, genetic
information, race, national origin, religion, sex, sexual orientation,
or status as a protected veteran.

Please see MathJobs (https://www.mathjobs.org/jobs/list/16684) for
application instructions. For further information, please contact
Boyce Griffith (boyceg@email.unc.edu).



From: James Adler james.adler@tufts.edu
Date: November 20, 2020
Subject: Postdoc Position, Computation of Soft Matter Physics, Tufts Univ


Theory/Computation Postdoctoral Scholar in Soft Matter

The Physics and Astronomy Department at Tufts University in Medford,
MA seeks a postdoctoral scholar to join a multidisciplinary NSF-funded
effort to create high performance numerical methods for studying shape
change in Soft Matter. The postdoc will be working with Tim Atherton
(Physics) and James Adler (Math) on a project to create an accessible
open-source software package, Morpho, able to solve a wide variety of
shape optimization, evolution and shapeshifting problems and build a
community using the software for their research. Further information
about the project is given below, and information on the PI's research
groups can be found at https://sites.tufts.edu/softmattertheory/ and
https://jadler.math.tufts.edu. The primary role of the postdoc will be
to apply the code to new scenarios involving shape change. An
important component will be working with other research groups, both
theoretical and experimental, to formulate, solve and adopt the
program in their own work as well as to identify functionality
required to solve new classes of problem. The postdoc will also have
considerable opportunity to work independently on problems of their
own within this general thematic area.

Please submit applications or questions about the position to
mailto:Timothy.atherton@tufts.edu by January 15th. Applications
beyond this date will still be accepted and reviewed on a continuous
basis until the position is filled. Please include a cover letter
outlining how your previous experience qualifies you for the position,
your CV/resume, contact information for two references and a brief
research statement.



From: Benjamin Peherstorfer pehersto@cims.nyu.edu
Date: November 23, 2020
Subject: Postdoc Position, Courant Institute of Mathematical Sciences, NYU


There is an open PostDoc position at Courant Institute of Mathematical
Sciences, New York University, in Benjamin Peherstorfer's group.

The topic of the position is scientific machine learning, i.e., the
intersection of machine learning and scientific computing. Topics of
particular interest include deep networks for PDE problems,
data-driven reduced-order modeling, and Monte Carlo and randomized
methods. Applications of interest are (Bayesian) inverse problems,
control, and uncertainty quantification (especially methods for
studying rare events). More details at https://cims.nyu.edu/~pehersto/

Candidates should have a PhD degree and have experience with applied
and computational mathematics, with a solid background in machine
learning and/or scientific computing. Candidates should have an
interest in science and engineering applications. The position has no
teaching requirement and is available with a flexible start date. The
initial appointment will be for one year, with the possibility of
yearly extensions depending on performance and funding.

Applications submitted by Dec 18, 2020 will receive full consideration
but the search will remain open until the position is filled. Please
contact pehersto@cims.nyu.edu for more details.

Documents to submit: Up-to-date CV with publication list, cover letter
explaining interests and goals, and 2 reference letters. More details
and formal application via Interfolio at
https://apply.interfolio.com/81354



From: Youssef Marzouk ymarz@mit.edu
Date: November 22, 2020
Subject: Postdoc Position, UQ for Quantum/Molecular Simulations, MIT


MIT's PSAAP simulation center (CESMIX: Center for Exascale Simulation
of Materials in Extreme Environments, http://cesmix.mit.edu) seeks a
postdoctoral scholar to advance uncertainty quantification (UQ)
methodologies for multiscale quantum and molecular simulation of
complex materials. The postdoctoral scholar will be directly
supervised by Youssef Marzouk (http://uqgroup.mit.edu), but will work
closely with an interdisciplinary team of faculty and researchers with
expertise in quantum chemistry, molecular dynamics, scientific
computing, and multiple aspects of computer science.

Successful applicants will hold a PhD in computational science and
engineering, applied mathematics, statistics, or a closely related
field. Applicants should have a record of research contributions to
uncertainty quantification methodology or related topics. Topics of
particular interest include Bayesian modeling and computation,
multi-fidelity modeling, approximate inference, optimal experimental
design, and model validation.

Prior experience with density functional theory and atomistic-level
simulation is helpful, but not required. Indeed, we are most
interested in candidates with strong backgrounds in mathematics and
statistics, a thoughtful perspective on modeling, and an appetite for
truly multi-disciplinary work. Experience contributing to open-source
software for statistics, scientific computing, and scientific machine
learning is also extremely desirable.

Successful candidates will also have excellent demonstrated written
and oral communication skills, and the ability to guide and mentor
graduate students.

To apply, please send a brief cover letter describing your interests,
a CV, and contact information for three references to . Applications
received by 11 December 2020 will be given priority.


From: Axel Voigt axel.voigt@tu-dresden.de
Date: November 23, 2020
Subject: PhD and Postpoc Position, Scientific Computing, TU Dresden


At the Faculty of Mathematics two positions are available at the
earliest possible date as a Research Associate (doctoral student or
postdoc) (Salary group E 13 collective labour agreement [TV-L] - when
the personal prerequisites are fulfilled) 75% or 100% of the regular
weekly working time for a period of three years. The positions are
part of the DFG research group 3013, which deals with the modelling,
numerics and simulation of vector- and tensor-valued partial
differential equations on surfaces. It connects worldwide leading
research groups in the fields of analysis, numerics as well as
modelling and simulation of continuum mechanical processes
(http://for3013.webspace.tu-dresden.de). We look for candidates
working on modeling and numerical aspects of surface Navier- Stokes
equations. The effects topology and curvature on flow properties are
of interest. The second project considers active polar and
nematodynamic models on surfaces, which are used to model the cellular
cortex and epithelia tissue. The following task complexes exist within
these two projects: Phase field formulation of problems to consider
topological changes (cell division), data analysis and quantitative
comparison with experiments, construction and investigation of finite
element methods for coupled systems of surface evolution and surface
fluids and implementation and integration of the developed methods
into existing software environments AMDiS/DUNE. Requirements:
scientific university degree in mathematics or a related field of
study. Good knowledge in the numerics of partial differential
equations and basic knowledge in differential geometry, and sound
knowledge of liquid crystal theory and phase field modeling, in the
theory of finite element methods, experience in programming in
C++. Applications with or without a PhD are expressly welcome. There
will be the opportunity to gain further academic
qualifications. Please send your application with the usual documents
(in particular a letter of recommendation) preferably via the
SecureMail Portal of TU Dresden https://securemail.tu-dresden.de as a
PDF document to axel.voigt@tu-dresden.de or by mail to TU Dresden,
Faculty of Mathematics, Institute of Scientific Computing,
Helmholtzstr. 10, 01069 Dresden. The application deadline is 20th
December 2020 (postmark of the ZPS of TU Dresden applies). Your
application documents will not be returned, therefore please submit
only copies.



From: Friederike Pollmann friederike.pollmann@uni-hamburg.de
Date: November 24, 2020
Subject: PhD Position, Ccean modeling/internal waves, Univ Hamburg


Universitat Hamburg invites applications for a PhD position in
theoretical oceanography. We are looking for a candidate with strong
analytical and programming skills, who is interested in applying them
to geoscience problems. The position will tackle internal gravity wave
energetics with a focus on theory and numerical modeling and the
overall goal of improving energy consistency in numerical ocean
models. The project is part of the collaborative research center "TRR
181: Energy transfers in atmosphere and ocean". Application deadline
is December 13th.

For details, please see
https://www.uni-hamburg.de/uhh/stellenangebote/wissenschaftliches-personal/=
fakultaet-
mathematik-informatik-und-naturwissenschaften/13-12-20-431-en.pdf

and for details about the project
https://www.trr-energytransfers.de



From: Marek Behr behr@cats.rwth-aachen.de
Date: November 23, 2020
Subject: PhD Position, Computational Engineering, RWTH Aachen Univ


The Chair for Computational Analysis of Technical Systems (CATS) [1]
at RWTH Aachen University (Germany) has an immediate opening for a
fully funded Ph.D. position at the intersection of engineering,
applied mathematics, and computer science, to work on novel stabilized
finite- element methods for microstructured and complex fluids. This
position is part of a Collaborative Research Center SFB 1120
"Precision Melt Engineering". The appointment at the payscale TV-L 13
(about 4000 euro per month gross at the entry level [2]) will be
initially for one year, and will be extended for two extra years upon
positive evaluation. Applications from excellent candidates are
invited. To apply, email the following documents to Prof. Marek Behr
(behr@cats.rwth-aachen.de): statement of purpose; detailed CV;
transcripts from your Bachelor and MS degrees; contact info of at
least two references; pointers to your previous publications and
projects (if any).

The review of applications is ongoing and will continue until the
position is filled.

[1]: http://www/cats/rwth-aachen.de
[2]: http://www.cats.rwth-aachen.de/cms/CATS/Der-
Lehrstuhl/Stellenangebote/~qspt/Stelleninfos/lidx/1/

Requirement for this position is a master's degree in CES,
engineering, applied mathematics, computer science, physics, or a
similar subject, with a superior academic record. Practical
programming experience in C or Fortran as well as with parallelization
are of advantage. Familiarity with UNIX operating system would be
ideal. Excellent written and spoken English language skills are
required.



From: Sean Hon seanyshon@hkbu.edu.hk
Date: November 20, 2020
Subject: PhD Position, Numerical Analysis, Hong Kong Baptist Univ


The Scientific Computing Group at Department of Mathematics invites
applications for a PhD position on numerical linear algebra.

The project focuses on developing fast iterative solvers for
time-dependent PDE problems. In particular, it aims at constructing
effective preconditioners for the Toepliz-like linear systems arising
from solving a wide range of PDEs, including wave equations, heat
equations, fractional diffusion equations, etc.

Applicants are expected to have solid knowledge in preconditioned
Krylov subspace methods and strong programming skills in MATLAB/C++.

Applicants are also encouraged to apply for a Hong Kong PhD
Fellowship, which offers substantial financial support to the
awardees. For details, read
https://gs.hkbu.edu.hk/f/page/281/HKPF%20leaflet%2020212022.pdf

The application deadline for both the PhD programme and the Fellowship
is December 1, 2020.

For informal enquiries, please contact Sean Hon at
seanyshon@hkbu.edu.hk

For application details, please visit
http://www.math.hkbu.edu.hk/RPg/

For more information about our research group, visit
http://www.math.hkbu.edu.hk/Research/research_SCgroups.html


From: Jose E Castillo jcastillo@sdsu.edu
Date: November 17, 2020
Subject: PhD Positions, Computational Data Science, USA


The Interdisciplinary Ph.D. Program in Computational Science is aimed
at training scientists and engineers who will create advanced
computational methods and tools to model and solve challenging
problems at the intersections of scientific disciplines. The doctoral
program offers coursework and research in a broad range of subjects
that develop expertise in Mathematical Modeling and Scientific
Computing with applications to Biological Science, Earth Science,
Engineering Science, Health, Physical and/or Chemical Science. UCI and
SDSU campuses are recognized as Hispanic Serving Institutions offering
a welcoming and supportive environment for diverse students. Admitted
graduate students are offered a range of financial assistance options
while they are pursuing advanced degrees, including Teaching,
Graduate, and Research Assistantships and Fellowships. Applicants with
strong backgrounds in mathematics, physical, biological and geological
sciences, computer science, and engineering are invited to apply.
Please check our website for details regarding the doctoral program
and the application process.

Website: http://www.csrc.sdsu.edu/csrc/doctoral.html



From: Matthias Ehrhardt ehrhardt@math.uni-wuppertal.de
Date: November 20, 2020
Subject: Industrial and Applied Mathematics, ONLINE, Apr 2021


ECMI 2021 conference

The ECMI 2021 Conference on Industrial and Applied Mathematics will be
held as an online conference hosted by the Bergische Universitat
Wuppertal from April 13th to April 15th 2021. The traditional
elements of a biennial ECMI conference such as plenary lectures, an
Anile prize lecture, a Wacker prize lecture, lectures within
minisymposia as well as contributed talks will be made available as
synchronous online events.

Unfortunately, because of the ongoing Corona pandemic, we were not be
able to have a normal face-to-face ECMI2020 at the University of
Limerick. Instead we are organizing a virtual ECMI2021 conference in
the period April 13-15, 2021, that will be as close as possible to the
traditional events.

A registration form will be made available soon on the conference
website where you can also submit a minisymposium proposal, a
minisymposium talk or a contributed talk.

As usual we will publish a conference proceedings Progress in
Industrial Mathematics at ECMI 2021, at Springer, see 'Submission' for
further details. Please follow the updates of this conference website
https://ecmi2021.uni-wuppertal.de/


From: Bryan Quaife bquaife@fsu.edu
Date: November 20, 2020
Subject: PhD and MS Positions, Computational Science, FSU


The Interdisciplinary Ph.D. Program in Computational Science develops
students into scientists and engineers who will create advanced
computational methods and tools to model and solve challenging
problems at the intersections of scientific disciplines. The doctoral
program offers coursework and research in a broad range of subjects
that develop expertise in Mathematical Modeling and Scientific
Computing with applications to Biological Science, Earth Science,
Engineering Science, Fire Dynamics, Health, Physical and/or Chemical
Science, and Robotics.

A brand new Interdisciplinary Masters Degree program in Data Science,
starting in Fall 2021, will offer students training in mathematics,
statistics, and machine learning.

Florida State University has been recognized as the top diversity
campus for the third consecutive year and is a tier-one Research
University. Admitted graduate students are offered a range of
financial assistance options including Teaching, and Research
Assistantships.

To be considered for funding, the deadline for application for the
Fall 2021 cohort is January 15, 2021, although one can apply until the
end of June 2021. Self-funded applicants interested in our 12 to 18
months Masters program in either Computational Science or Data Science
will be considered throughout the Spring Semester.

Email: sc-advising@sc.fsu.edu
Application: https://www.sc.fsu.edu/graduate/application



From: Wei Cai CAI@SMU.EDU
Date: November 18, 2020
Subject: Contents, CiCP Special Issue, ML for Scientific Computing


A special issue on Machine Learning for Scientific Computing is now
published online and CiCP (Communications in Computational Physics) is
making it available to the general scientific community at

https://www.global-sci.org/intro/articles_list.html?journal=3Dcicp&volume_i=
d=3D2044


1. Machine Learning and Computational Mathematics, Weinan E

2. Dying ReLU and Initialization: Theory and Numerical Examples, Lu
Lu, Yeonjong Shin, Yanhui Su & George Em Karniadakis

3. Finite Neuron Method and Convergence Analysis, Jinchao Xu

4. Frequency Principle: Fourier Analysis Sheds Light on Deep Neural
Networks, Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo, Yanyang Xiao & Zheng
Ma

5. Deep Network Approximation Characterized by Number of Neurons,
Zuowei Shen, Haizhao Yang & Shijun Zhang

6. Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process
Regression, Yixiang Deng, Guang Lin & Xiu Yang

7. Butterfly-Net: Optimal Function Representation Based on
Convolutional Neural Networks, Yingzhou Li, Xiuyuan Cheng & Jianfeng
Lu

8. A Multi-Scale DNN Algorithm for Nonlinear Elliptic Equations with
Multiple Scales, Xi-An Li, Zhi-Qin John Xu & Lei Zhang

9. Random Batch Algorit,hms for Quantum Monte Carlo Simulations Shi
Jin & Xiantao Li

10. High-Dimensional Nonlinear Multi-Fidelity Model with Gradient-Free
Active Subspace Method, Bangde Liu & Guang Lin

11. Multi-Scale Deep Neural Network (MscaleDNN) for Solving Poisson-
Boltzmann Equation in Complex Domains, Ziqi Liu, Wei Cai & Zhi-Qin
John Xu

12. Extended Physics-Informed Neural Networks (XPINNs): A Generalized
Space-Time Domain Decomposition Based Deep Learning Framework for
Nonlinear Partial Differential Equations, Ameya D. Jagtap & George Em
Karniadakis

13. On the Convergence of Physics Informed Neural Networks for Linear
Second-Order Elliptic and Parabolic Type PDEs, Yeonjong Shin, Jerome
Darbon & George Em Karniadakis

14. Convolution Neural Network Shock Detector for Numerical Solution
of Conservation Laws, Zheng Sun, Shuyi Wang, Lo-Bin Chang, Yulong Xing
& Dongbin Xiu

15. Numerical Simulations for Full History Recursive Multilevel Picard
Approximations for Systems of High-Dimensional Partial Differential
Equations, Sebastian Becker, Ramon Braunwarth, Martin Hutzenthaler,
Arnulf Jentzen & Philippe von Wurstemberger

16. Multi-Scale Deep Neural Network (MscaleDNN) Methods for
Oscillatory Stokes Flows in Complex Domains, Bo Wang, Wenzhong Zhang &
Wei Cai

17. Learning to Discretize: Solving 1D Scalar Conservation Laws via
Deep Reinforcement Learning, Yufei Wang, Ziju Shen, Zichao Long & Bin
Dong

18. An Adaptive Surrogate Modeling Based on Deep Neural Networks for
Large-Scale Bayesian Inverse Problems, Liang Yan & Tao Zhou



From: Yonghui Yu yyu@lsec.cc.ac.cn
Date: November 24, 2020
Subject: Contents, Computational Mathematics, 38 (6)


Journal of Computational Mathematics, Volume 38 (2020), Issue 6

CONTENTS

An Extended Block Restricted Isometry Property for Sparse Recovery
with Non-Gaussian Noise, Klara Leffler, Zhiyong Zhou and Jun Yu

Discontinuous Galerkin Methods and Their Adaptivity for the Tempered
Fractional (Convection) Diffusion Equations, Xudong Wang and Xudong
Wang

The Plateau-B'ezier Problem with Weak-Area Functional, Yongxia Hao

Two-variable Jacobi Polynomials for Solving Some Fractional Partial
Differential Equations, Jafar Biazar and Khadijeh Sadri

Convergence Rate of the Truncated Euler-Maruyama Method for Neutral
Stochastic Differential Delay Equations with Markovian Switching, Wei
Zhang

Solution of Optimal Transportation Problems Using a Multigrid Linear
Programming Approach, Adam M. Oberman and Yuanlong Ruan

Convergence of Laplacian Spectra from Random Samples, Wenqi Tao and
Zuoqiang Shi

End of Digest
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