DOCSLIB.ORG

NSF Annual Report

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
NSF Annual Report NSF Annual Report 2007-2008 Submitted to the National Science Foundation April 30, 2008 1 NSF Annual Progress Report for 2007-2008 As outlined in the terms of grant DMS-0635449, the following is the Annual Progress Report for the Statistical and Applied Mathematical Sciences Institute (SAMSI), for the period August 15, 2007 – July 31, 2008. Past activities that concluded during this period and future activities of SAMSI are also discussed. 0. Executive Summary A. Outline of Activities and Initiatives for 2007-2008 and the Future................................. B. Financial Overview .......................................................................................................... C. Directorate’s Summary of Challenges and Responses..................................................... D. Synopsis of Research, Human Resource Development, and Education.......................... E. Evaluation by the SAMSI Governing Board.................................................................... Annual Report Table of Contents.......................................................................................... A. Outline of Activities and Initiatives 1. 2007-2008 Programs and Activities • Summer Program on Geometry and Statistics of Shape Spaces (July 7-13, 2007) o Tutorials (7/8/07-7/9/07) o Opening Workshop (7/10/07-7/12/07) • Risk Analysis, Extreme Events and Decision Theory (Fall 2007, Spring 2008) o Opening Workshop and Tutorials (9/16/07-9/19/07) o Workshop on Risk: Perception, Policy and Practice (10/3/07-10/04/07) o Workshop on Extremes: Events, Models and Mathematical Theory (1/22- 24/08) o Transition Workshop (5/21/08) • Random Media (Fall 2007, Spring 2008) o Opening Workshop and Tutorials (9/23/07-9/26/07) o Interface Problems Workshop (11/15/07-11/16/07) o Waves and Imaging Workshop (1/31/08-2/1/08) o Transition Workshop (5/1/08-5/2/08) • Environmental Sensor Networks (Spring 2008) o Opening Workshop (1/13/08-1/16/08) o Transition workshop (10/20/08-10/21/08) • Summer Program on Meta-analysis: Synthesis and Appraisal of Multiple Sources of Empirical Evidence (June 2-13, 2008) o Tutorials (6/2/08-6/4/08) o Opening Workshop (6/5/08-6/6/08) 2 Education and Outreach • 2-Day Workshop for Undergraduates (11/9/07-11/10/07) • Infinite Possibilities Workshop (11/2/07-11/3/07) • 2-Day Workshop for Undergraduates (2/29/08-3/1/08)) • Interdisciplinary Workshop for Undergraduates (5/19/08-5/23/08) • The Industrial Mathematical and Statistical Modeling Workshop for Graduate Students (7/21/08-7/29/08) • Graduate Courses at SAMSI o Decision Theory and Risk Analysis, Fall 2007 o Numerical Methods for Free Boundary and Moving Interfaces, Fall 2007 o Sensor Networks for Environmental Monitoring, Fall 2008 o Extremes and Cases Studies in Risk Analysis, Spring 2008 Planning and Brainstorming Meetings • Cyber-enabled Discovery and Innovation Workshop (11/1/07) 2. 2008-2009 Programs and Activities Schedule • Algebraic Methods in Systems Biology and Statistics (Fall 2008, Spring 2009) o Opening Workshop and Tutorials (9/14/08-9/17/08) o Mid-Program Workshops: TBD o Transition Workshop (mid-June, 2009) • Sequential Monte Carlo Methods (Fall 2008, Spring 2009, Summer, 2009 ) o Opening Workshop and Tutorials (9/7/08-9/10/08) o Mid-Program Workshop: TBD o Workshop on Multi-Sensor Multi-Target Tracking and Data Fusion (4/09) o Transition Workshop (10/5/09-10/6/09) • Summer Program in 2009: TBD Education and Outreach • 2-Day Workshop for Undergraduates (10/31/08-11/1/08) • Blackwell-Tapia Conference (11/14/08-11/15/08) • 2-Day Workshop for Undergraduates (2/27/09-2/28/09) • Interdisciplinary Workshop for Undergraduates (5/18/09-5/22/09) • The Industrial Mathematical and Statistical Modeling Workshop for Graduate Students (7/21/09-7/29/09) • Graduate Courses at SAMSI o Sequential Monte Carlo Methods, Fall 2008 o Algebraic Methods in Systems Biology and Statistics, Fall 2007 3. Tentative Programs for 2009-2010 • Stochastic Dynamics • Space-time Analysis for Environmental Mapping, Epidemiology and Climate Change 3 4. Developments and Initiatives • The plan for expansion of space, through an addition to the NISS building, was completed and construction is under way. • An NAC Scientific Advisory Board is being created to provide input into the initiation and development of interdisciplinary SAMSI programs. • The new Kenan K-12 Mentor program was initiated. • Michael Minion joined the SAMSI Directorate, replacing Chris Jones • A new administrative structure was implemented o An Assistant Director position was created to manage activities; Denise Auger was appointed to the position. o Rita Fortune was appointed as the financial Administrative Assistant. o Sue McDonald was appointed as the Administrative Assistant for program development. o A part-time Communications Specialist is being added. • Additional research collaborations with other institutes were initiated to enhance the overall impact of mathematics and statistics: o Activities with the National Center for Atmospheric Research have continued, including two joint postdoctoral appointments. o SAMSI in planning a variety of activities with the Canadian National Program on Complex Data Structures, involving their proposed new institute (the National Institute for Complex Data Structures). o Agreement was reached with the Virtual Center for collaboration of visitors between the US and China to potentially provide airfares for Chinese visitors to SAMSI. 4 C. Directorate’s Summary of Challenges and Responses As we proceed through the first year of the 5-year renewal grant, SAMSI has continued to be successful in achieving its’ goals. The scientific programs have been of high caliber, and have led to significant new and ongoing research collaborations between, statistics, applied mathematics, and disciplinary sciences. There has been significant human resource development, through the postdoctoral and graduate programs and through involvement of senior researchers in new interdisciplinary areas. Many students across the country have been shown the SAMSI vision through educational outreach programs and courses. We feel that these successes are amply demonstrated throughout the report; some highlights are given in section D of the Executive Summary. This section discusses the challenges that arose this year and the Directorate’s response to these challenges. Building Addition: Our biggest challenge at SAMSI over the past two years has been a lack of space. Offices (meant for one person) sometimes were occupied by three. Furthermore, there was simply no room for local scientists to reside at SAMSI, which meant that their participation was mostly limited to the formal working group meetings, as opposed to the informal interactions and mentoring that can happen when resident. Meeting space has also been a severe problem. Our largest current meeting room holds only 35 people, which precluded holding many workshops on site. There was also a shortage of meeting space for the Research Working Groups; these groups now have many external members, who connect to the working group meetings over our web-based system. We currently have only one room that is properly equipped for these web-based meetings, making scheduling of all the working group meetings a logistics nightmare. With the renewal of SAMSI, we were able to proceed with the plan to address this major problem by fast-tracking the planning and preparation for the long-awaited addition to the NISS/SAMSI building. NISS, which is undertaking the building addition, and especially NISS Director Alan Karr – who was the key figure in this planning and implementation – are owed a great debt of gratitude by SAMSI. Groundbreaking took place on November 2, 2007, and construction began in February of 2008. The addition will be complete in early Fall 2008, hopefully in time for the influx of people for the 2008-2009 programs. The 11,782 square foot addition will effectively double SAMSI’s office space, allowing more visitors and stronger engagement by program participants from the Research Triangle universities. The addition will also contain space to be shared by SAMSI and NISS, including a break room and accompanying rooftop terrace and a 50-seat lecture room. The lecture room will change dramatically the scale and nature of SAMSI events held on-site. Not only does it double the number of in-person participants, but also it will provide state-of-the art electronic capabilities that enable even more remote participation in SAMSI workshops and working group meetings. An ongoing photographic log of the construction process is available on the NISS web site, at http://www.niss.org/photogallery/construction2008/construction08-home.html. 5 Figure 1: The "official" groundbreakers. Left to right: SAMSI Governing Board Chair Daniel Solomon, incoming NISS Board Chair James Landwehr, NISS Building Committee chair Jon Kettenring, NISS and SAMSI Associate Director Nell Sedransk, SAMSI Director James Berger and NISS Director Alan Karr. Figure 2: Elevations for the addition to the NISS/SAMSI building. 6 National Leadership and Involvement: SAMSI programs continue to have primarily national leadership. Of course, these programs still have significant participation of local scientists; indeed, one of the major strengths of SAMSI is its’ ability to draw to its programs stellar local talent in applied mathematics, statistics, and disciplinary sciences. The Education and Outreach program was broadened in terms of national scope, in several ways. First, the Education and Outreach
Load more

Recommended publications
  • Royal Statistical Scandal
    Royal Statistical Scandal False and misleading claims by the Royal Statistical Society Including on human poverty and UN global goals Documentary evidence Matt Berkley Draft 27 June 2019 1 "The Code also requires us to be competent. ... We must also know our limits and not go beyond what we know.... John Pullinger RSS President" https://www.statslife.org.uk/news/3338-rss-publishes-revised-code-of- conduct "If the Royal Statistical Society cannot provide reasonable evidence on inflation faced by poor people, changing needs, assets or debts from 2008 to 2018, I propose that it retract the honour and that the President makes a statement while he holds office." Matt Berkley 27 Dec 2018 2 "a recent World Bank study showed that nearly half of low-and middle- income countries had insufficient data to monitor poverty rates (2002- 2011)." Royal Statistical Society news item 2015 1 "Max Roser from Oxford points out that newspapers could have legitimately run the headline ' Number of people in extreme poverty fell by 137,000 since yesterday' every single day for the past 25 years... Careless statistical reporting could cost lives." President of the Royal Statistical Society Lecture to the Independent Press Standards Organisation April 2018 2 1 https://www.statslife.org.uk/news/2495-global-partnership-for- sustainable-development-data-launches-at-un-summit 2 https://www.statslife.org.uk/features/3790-risk-statistics-and-the-media 3 "Mistaken or malicious misinformation can change your world... When the government is wrong about you it will hurt you too but you may never know how.
    [Show full text]
  • The Fourth Paradigm
    ABOUT THE FOURTH PARADIGM This book presents the first broad look at the rapidly emerging field of data- THE FOUR intensive science, with the goal of influencing the worldwide scientific and com- puting research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud- computing technologies. This collection of essays expands on the vision of pio- T neering computer scientist Jim Gray for a new, fourth paradigm of discovery based H PARADIGM on data-intensive science and offers insights into how it can be fully realized. “The impact of Jim Gray’s thinking is continuing to get people to think in a new way about how data and software are redefining what it means to do science.” —Bill GaTES “I often tell people working in eScience that they aren’t in this field because they are visionaries or super-intelligent—it’s because they care about science The and they are alive now. It is about technology changing the world, and science taking advantage of it, to do more and do better.” —RhyS FRANCIS, AUSTRALIAN eRESEARCH INFRASTRUCTURE COUNCIL F OURTH “One of the greatest challenges for 21st-century science is how we respond to this new era of data-intensive
    [Show full text]
  • A Complete Bibliography of Publications in SIAM Journal on Mathematical Analysis, 1970–1999
    A Complete Bibliography of Publications in SIAM Journal on Mathematical Analysis, 1970{1999 Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 13 March 2018 Version 3.14 ∗ Title word cross-reference aK(at);a! 0 [Log79b]. B [Rei79]. BC1 [Ask82]. β [HT87]. BV (Ω) [AK99]. C1 [Coh89]. C3 [McC97]. Cα [YL94]. Cα(Ω) [XA91]. Cp [Rea86b]. C [Yao95]. C (T ) #11889 [Spe79]. 0 0 [Wu90]. C` [Mil94]. A [FM99]. D [Har80]. D O(2) [ML93]. Dr u(x; t)=D u(x; t) (−1; 1) [LS93]. (−∞; 1)[Pas74]. n x t 0 0 [Kem82a]. (m(t)x (t)) + A(t)x(t)=0[Ede79]. k ∗ 0 0 0 D U(X1; ···;Xr)=DX U(X1; ···;Xr) (p(x)u (x)) + g(x)u (x)+qu(x)=f [Whi79]. X1 k [Kem85]. DA [Har80]. δ [Lan83b]. ∆2u = λu (φ(y0)) = qf(t; y; y0); 0 <t<1[O'R93]. [Cof82]. ∆ u(x)+F (x)u(x)=0[CG71]. (r(t) (x)x0)0 + a(t)f(x) = 0 [MR79a]. p+2 ∆ + K2 = 0 [Kal75]. 0 <p(x) 2 L1[a; b] [Whi79]. 0 ≤ x ≤ l − ∆u + K(jxj)jujp 1u = 0 [Yan96]. [CL73]. 2 [AJV94, CW99]. 2m + 1 [Sho70]. − − ∆u + jujp 1u −|ujq 1u = 0 [Tro90]. E3 2π [FR91]. 2π/m [FR91]. 3 [KoM98].
    [Show full text]
  • Writing the History of Dynamical Systems and Chaos
    Historia Mathematica 29 (2002), 273–339 doi:10.1006/hmat.2002.2351 Writing the History of Dynamical Systems and Chaos: View metadata, citation and similar papersLongue at core.ac.uk Dur´ee and Revolution, Disciplines and Cultures1 brought to you by CORE provided by Elsevier - Publisher Connector David Aubin Max-Planck Institut fur¨ Wissenschaftsgeschichte, Berlin, Germany E-mail: [email protected] and Amy Dahan Dalmedico Centre national de la recherche scientifique and Centre Alexandre-Koyre,´ Paris, France E-mail: [email protected] Between the late 1960s and the beginning of the 1980s, the wide recognition that simple dynamical laws could give rise to complex behaviors was sometimes hailed as a true scientific revolution impacting several disciplines, for which a striking label was coined—“chaos.” Mathematicians quickly pointed out that the purported revolution was relying on the abstract theory of dynamical systems founded in the late 19th century by Henri Poincar´e who had already reached a similar conclusion. In this paper, we flesh out the historiographical tensions arising from these confrontations: longue-duree´ history and revolution; abstract mathematics and the use of mathematical techniques in various other domains. After reviewing the historiography of dynamical systems theory from Poincar´e to the 1960s, we highlight the pioneering work of a few individuals (Steve Smale, Edward Lorenz, David Ruelle). We then go on to discuss the nature of the chaos phenomenon, which, we argue, was a conceptual reconfiguration as
    [Show full text]
  • Program of the Sessions San Diego, California, January 9–12, 2013
    Program of the Sessions San Diego, California, January 9–12, 2013 AMS Short Course on Random Matrices, Part Monday, January 7 I MAA Short Course on Conceptual Climate Models, Part I 9:00 AM –3:45PM Room 4, Upper Level, San Diego Convention Center 8:30 AM –5:30PM Room 5B, Upper Level, San Diego Convention Center Organizer: Van Vu,YaleUniversity Organizers: Esther Widiasih,University of Arizona 8:00AM Registration outside Room 5A, SDCC Mary Lou Zeeman,Bowdoin upper level. College 9:00AM Random Matrices: The Universality James Walsh, Oberlin (5) phenomenon for Wigner ensemble. College Preliminary report. 7:30AM Registration outside Room 5A, SDCC Terence Tao, University of California Los upper level. Angles 8:30AM Zero-dimensional energy balance models. 10:45AM Universality of random matrices and (1) Hans Kaper, Georgetown University (6) Dyson Brownian Motion. Preliminary 10:30AM Hands-on Session: Dynamics of energy report. (2) balance models, I. Laszlo Erdos, LMU, Munich Anna Barry*, Institute for Math and Its Applications, and Samantha 2:30PM Free probability and Random matrices. Oestreicher*, University of Minnesota (7) Preliminary report. Alice Guionnet, Massachusetts Institute 2:00PM One-dimensional energy balance models. of Technology (3) Hans Kaper, Georgetown University 4:00PM Hands-on Session: Dynamics of energy NSF-EHR Grant Proposal Writing Workshop (4) balance models, II. Anna Barry*, Institute for Math and Its Applications, and Samantha 3:00 PM –6:00PM Marina Ballroom Oestreicher*, University of Minnesota F, 3rd Floor, Marriott The time limit for each AMS contributed paper in the sessions meeting will be found in Volume 34, Issue 1 of Abstracts is ten minutes.
    [Show full text]
  • Prizes and Awards Session
    PRIZES AND AWARDS SESSION Wednesday, July 12, 2021 9:00 AM EDT 2021 SIAM Annual Meeting July 19 – 23, 2021 Held in Virtual Format 1 Table of Contents AWM-SIAM Sonia Kovalevsky Lecture ................................................................................................... 3 George B. Dantzig Prize ............................................................................................................................. 5 George Pólya Prize for Mathematical Exposition .................................................................................... 7 George Pólya Prize in Applied Combinatorics ......................................................................................... 8 I.E. Block Community Lecture .................................................................................................................. 9 John von Neumann Prize ......................................................................................................................... 11 Lagrange Prize in Continuous Optimization .......................................................................................... 13 Ralph E. Kleinman Prize .......................................................................................................................... 15 SIAM Prize for Distinguished Service to the Profession ....................................................................... 17 SIAM Student Paper Prizes ....................................................................................................................
    [Show full text]
  • Spatio-Temporal Point Processes: Methods and Applications Peter J
    Johns Hopkins University, Dept. of Biostatistics Working Papers 6-27-2005 Spatio-temporal Point Processes: Methods and Applications Peter J. Diggle Medical Statistics Unit, Lancaster University, UK & Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, [email protected] Suggested Citation Diggle, Peter J., "Spatio-temporal Point Processes: Methods and Applications" (June 2005). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 78. http://biostats.bepress.com/jhubiostat/paper78 This working paper is hosted by The Berkeley Electronic Press (bepress) and may not be commercially reproduced without the permission of the copyright holder. Copyright © 2011 by the authors Spatio-temporal Point Processes: Methods and Applications Peter J Diggle (Department of Mathematics and Statistics, Lancaster University and Department of Biostatistics, Johns Hopkins University School of Public Health) June 27, 2005 1 Introduction This chapter is concerned with the analysis of data whose basic format is (xi; ti) : i = 1; :::; n where each xi denotes the location and ti the corresponding time of occurrence of an event of interest. We shall assume that the data form a complete record of all events which occur within a pre-specified spatial region A and a pre-specified time- interval, (0; T ). We call a data-set of this kind a spatio-temporal point pattern, and the underlying stochastic model for the data a spatio-temporal point process. 1.1 Motivating examples 1.1.1 Amacrine cells in the retina of a rabbit One general approach to analysing spatio-temporal point process data is to extend existing methods for purely spatial data by considering the time of occurrence as a distinguishing feature, or mark, attached to each event.
    [Show full text]
  • Society Reports USNC/TAM
    Appendix J 2008 Society Reports USNC/TAM Table of Contents J.1 AAM: Ravi-Chandar.............................................................................................. 1 J.2 AIAA: Chen............................................................................................................. 2 J.3 AIChE: Higdon ....................................................................................................... 3 J.4 AMS: Kinderlehrer................................................................................................. 5 J.5 APS: Foss................................................................................................................. 5 J.6 ASA: Norris............................................................................................................. 6 J.7 ASCE: Iwan............................................................................................................. 7 J.8 ASME: Kyriakides.................................................................................................. 8 J.9 ASTM: Chona ......................................................................................................... 9 J.10 SEM: Shukla ....................................................................................................... 11 J.11 SES: Jasiuk.......................................................................................................... 13 J.12 SIAM: Healey...................................................................................................... 14 J.13 SNAME: Karr....................................................................................................
    [Show full text]
  • Sequential Monte Carlo Methods for Inference and Prediction of Latent Time-Series
    SSStttooonnnyyy BBBrrrooooookkk UUUnnniiivvveeerrrsssiiitttyyy The official electronic file of this thesis or dissertation is maintained by the University Libraries on behalf of The Graduate School at Stony Brook University. ©©© AAAllllll RRRiiiggghhhtttsss RRReeessseeerrrvvveeeddd bbbyyy AAAuuuttthhhooorrr... Sequential Monte Carlo Methods for Inference and Prediction of Latent Time-series A Dissertation presented by Iñigo Urteaga to The Graduate School in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Electrical Engineering Stony Brook University August 2016 Stony Brook University The Graduate School Iñigo Urteaga We, the dissertation committee for the above candidate for the Doctor of Philosophy degree, hereby recommend acceptance of this dissertation. Petar M. Djuri´c,Dissertation Advisor Professor, Department of Electrical and Computer Engineering Mónica F. Bugallo, Chairperson of Defense Associate Professor, Department of Electrical and Computer Engineering Yue Zhao Assistant Professor, Department of Electrical and Computer Engineering Svetlozar Rachev Professor, Department of Applied Math and Statistics This dissertation is accepted by the Graduate School. Nancy Goroff Interim Dean of the Graduate School ii Abstract of the Dissertation Sequential Monte Carlo Methods for Inference and Prediction of Latent Time-series by Iñigo Urteaga Doctor of Philosophy in Electrical Engineering Stony Brook University 2016 In the era of information-sensing mobile devices, the Internet- of-Things and Big Data, research on advanced methods for extracting information from data has become extremely critical. One important task in this area of work is the analysis of time-varying phenomena, observed sequentially in time. This endeavor is relevant in many applications, where the goal is to infer the dynamics of events of interest described by the data, as soon as new data-samples are acquired.
    [Show full text]
  • Letter from the RSS Covid-19 Task Force To
    Letter from the Royal Statistical Society Covid-19 Task Force to the Guardian regarding data transparency 7 August 2020 The Covid-19 public health crisis has placed a sharp emphasis on the role of data in government decision-making. During the current phase – where the emphasis is on Test and Trace and local lockdowns – data is playing an increasingly central role in informing policy. We recognise that the stakes are high and that decisions need to be made quickly. However, this makes it even more important that data is used in a responsible and effective manner. Transparency around the data that are being used to inform decisions is central to this. Over the past week, there have been two major data-led government announcements where the supporting data were not made available at the time. First, the announcement that home and garden visits would be made illegal in parts of northern England. The Prime Minister cited unpublished data which suggested that these visits were the main setting for transmission. Second, the purchase of two new tests for the virus that claim to deliver results within 90 minutes, without data regarding the tests’ effectiveness being published. We are concerned about the lack of transparency in these two cases – these are important decisions and the data upon which they are based should be publicly available for scrutiny, as Paul Nurse pointed out in this paper at the weekend. Government rhetoric often treats data as a managerial tool for informing decisions. But beyond this, transparency and well sign-posted data builds public trust and encourages compliance: the daily provision of statistical information was an integral part of full lockdown and was both expected and valued by the public.
    [Show full text]
  • YALE Environmental NEWS
    yale environmental n e w s The Yale Peabody Museum of Natural History, the School of Forestry & Environmental Studies, and the Yale Institute for Biospheric Studies spring 2008 · vol. 13, no. 2 Greetings from New YIBS Director Jeffrey Park see page 2 News from the Director of YIBS By Jeffrey Park RoseRita Riccitelli I was honored last autumn to be asked to serve as the Director of Yale’s faculty positions in Ecology & Evolutionary search for extraterrestrial life. An interdepart- at present, and a substantial public outreach Institute for Biospheric Studies by President Richard Levin and Provost Biology, and each year awards Gaylord mental hiring initiative in the broad field of effort has been proposed for the center. The Donnelley environmental postdoctoral fellow- microbiology has been presented to the Dean final form of the proposed institute is subject Andrew Hamilton. ships to researchers in the biodiversity of both of Yale College and the Provost. Establishing a to many uncertainties. At this stage of plan- our present world and in the geologic past. multi-departmental faculty cluster in the newly ning, however, one thing is clear: YIBS will play I have had the great benefit of succeeding That was 2004. This is 2008 and the stakes we YIBS seeded a faculty position in Geology acquired laboratories of Yale’s West Campus is an important role if the Yale Climate Institute Derek Briggs, whose able leadership of YIBS face are larger. The twin pressures on global & Geophysics, maintaining Yale’s leading one possible outcome of this effort. becomes a reality. has given me momentum and guidance for agriculture exerted by the developing world’s scholarship in how climate and atmospheric Biospheric studies at Yale serves broadly The Winter/Spring 2008 semester has the future.
    [Show full text]
  • Gareth Roberts
    Publication list: Gareth Roberts [1] Hongsheng Dai, Murray Pollock, and Gareth Roberts. Bayesian fusion: Scalable unification of distributed statistical analyses. arXiv preprint arXiv:2102.02123, 2021. [2] Christian P Robert and Gareth O Roberts. Rao-blackwellization in the mcmc era. arXiv preprint arXiv:2101.01011, 2021. [3] Dootika Vats, Fl´avioGon¸calves, KrzysztofLatuszy´nski,and Gareth O Roberts. Efficient Bernoulli factory MCMC for intractable likelihoods. arXiv preprint arXiv:2004.07471, 2020. [4] Marcin Mider, Paul A Jenkins, Murray Pollock, Gareth O Roberts, and Michael Sørensen. Simulating bridges using confluent diffusions. arXiv preprint arXiv:1903.10184, 2019. [5] Nicholas G Tawn and Gareth O Roberts. Optimal temperature spacing for regionally weight-preserving tempering. arXiv preprint arXiv:1810.05845, 2018. [6] Joris Bierkens, Kengo Kamatani, and Gareth O Roberts. High- dimensional scaling limits of piecewise deterministic sampling algorithms. arXiv preprint arXiv:1807.11358, 2018. [7] Cyril Chimisov, Krzysztof Latuszynski, and Gareth Roberts. Adapting the Gibbs sampler. arXiv preprint arXiv:1801.09299, 2018. [8] Cyril Chimisov, Krzysztof Latuszynski, and Gareth Roberts. Air Markov chain Monte Carlo. arXiv preprint arXiv:1801.09309, 2018. [9] Paul Fearnhead, Krzystof Latuszynski, Gareth O Roberts, and Giorgos Sermaidis. Continuous-time importance sampling: Monte Carlo methods which avoid time-discretisation error. arXiv preprint arXiv:1712.06201, 2017. [10] Fl´avioB Gon¸calves, Krzysztof GLatuszy´nski,and Gareth O Roberts. Exact Monte Carlo likelihood-based inference for jump-diffusion processes. arXiv preprint arXiv:1707.00332, 2017. [11] Andi Q Wang, Murray Pollock, Gareth O Roberts, and David Stein- saltz. Regeneration-enriched Markov processes with application to Monte Carlo. to appear in Annals of Applied Probability, 2020.
    [Show full text]