咨询与建议

限定检索结果

文献类型

  • 419 篇 期刊文献
  • 58 篇 会议
  • 1 册 图书

馆藏范围

  • 478 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 368 篇 理学
    • 212 篇 物理学
    • 151 篇 数学
    • 72 篇 化学
    • 64 篇 统计学(可授理学、...
    • 48 篇 生物学
    • 30 篇 系统科学
    • 9 篇 天文学
  • 303 篇 工学
    • 106 篇 计算机科学与技术...
    • 75 篇 软件工程
    • 57 篇 力学(可授工学、理...
    • 54 篇 化学工程与技术
    • 48 篇 材料科学与工程(可...
    • 37 篇 电子科学与技术(可...
    • 34 篇 信息与通信工程
    • 33 篇 动力工程及工程热...
    • 32 篇 控制科学与工程
    • 32 篇 生物工程
    • 29 篇 电气工程
    • 25 篇 生物医学工程(可授...
    • 19 篇 机械工程
    • 19 篇 光学工程
    • 12 篇 仪器科学与技术
    • 11 篇 核科学与技术
    • 10 篇 冶金工程
    • 9 篇 航空宇航科学与技...
  • 30 篇 管理学
    • 19 篇 管理科学与工程(可...
    • 11 篇 工商管理
    • 11 篇 图书情报与档案管...
  • 15 篇 医学
    • 12 篇 基础医学(可授医学...
    • 9 篇 临床医学
  • 7 篇 法学
  • 7 篇 农学
  • 3 篇 经济学
  • 3 篇 教育学

主题

  • 10 篇 density function...
  • 9 篇 gravitational wa...
  • 8 篇 molecular dynami...
  • 5 篇 machine learning
  • 5 篇 fluid structure ...
  • 5 篇 gravitational wa...
  • 4 篇 dynamical system...
  • 4 篇 deep learning
  • 4 篇 microstructure
  • 4 篇 neural networks
  • 4 篇 first-principles...
  • 4 篇 hydrodynamics
  • 4 篇 diffusion
  • 4 篇 stochastic syste...
  • 4 篇 artificial neura...
  • 4 篇 gravitational wa...
  • 3 篇 noise measuremen...
  • 3 篇 density function...
  • 3 篇 ground state
  • 3 篇 hamiltonians

机构

  • 29 篇 program in appli...
  • 23 篇 program in appli...
  • 18 篇 department of ch...
  • 15 篇 institute for pl...
  • 14 篇 university of so...
  • 14 篇 program in appli...
  • 14 篇 indian institute...
  • 14 篇 carolina center ...
  • 13 篇 université libre...
  • 12 篇 department of as...
  • 12 篇 scuola di ingegn...
  • 12 篇 infn sezione di ...
  • 12 篇 dipartimento di ...
  • 12 篇 università degli...
  • 12 篇 department of ph...
  • 12 篇 infn trento inst...
  • 12 篇 max planck insti...
  • 12 篇 université paris...
  • 12 篇 universiteit gen...
  • 12 篇 gran sasso scien...

作者

  • 16 篇 griffith boyce e...
  • 16 篇 kevrekidis ioann...
  • 16 篇 weinan e.
  • 15 篇 zhang linfeng
  • 13 篇 yue zhao
  • 12 篇 r. takahashi
  • 12 篇 j. c. bayley
  • 12 篇 k. komori
  • 12 篇 t. kajita
  • 12 篇 f. hellman
  • 12 篇 m. kinley-hanlon
  • 12 篇 t. mcrae
  • 12 篇 a. parisi
  • 12 篇 t. sawada
  • 12 篇 s. rowan
  • 12 篇 s. m. aronson
  • 12 篇 v. p. mitrofanov
  • 12 篇 g. moreno
  • 12 篇 g. hemming
  • 12 篇 p. fritschel

语言

  • 452 篇 英文
  • 25 篇 其他
  • 1 篇 德文
  • 1 篇 法文
  • 1 篇 中文
检索条件"机构=Department of Chemical Engineering and Program in Applied and COmputational Mathematics"
478 条 记 录,以下是111-120 订阅
排序:
An Immersed Interface Method for Incompressible Flows and Geometries with Sharp Features
arXiv
收藏 引用
arXiv 2024年
作者: Facci, Michael J. Kolahdouz, Ebrahim M. Griffith, Boyce E. Department of Mathematics University of North Carolina Chapel HillNC United States Flatiron Institute Simons Foundation New YorkNY United States Department of Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina School of Medicine Chapel HillNC United States McAllister Heart Institute University of North Carolina School of Medicine Chapel HillNC United States
The immersed interface method (IIM) for models of fluid flow and fluid-structure interaction imposes jump conditions that capture stress discontinuities generated by forces that are concentrated along immersed boundar... 详细信息
来源: 评论
Estimation of the main air pollutants from different biomasses under combustion atmospheres by artificial neural networks
收藏 引用
Chemosphere 2024年 352卷 141484页
作者: Monteiro, Thalyssa Oliveira Alves, Pedro Augusto Araújo da Silva de Almeida Nava Barradas Filho, Alex Oliveira Villa-Vélez, Harvey Alexander Cruz, Glauber Postgraduate Program in Mechanical Engineering (PPGMEC) Department of Mechanics and Materials Federal Institute of Education Science and Technology of Maranhão (IFMA) Maranhão São Luís Brazil Postgraduate Program in Computer Science and Computational Mathematics (PPG-CCMC) Department of Computer Science University of São Paulo (USP) São Carlos São Paulo Brazil Data Analysis and Artificial Intelligence Laboratory (DARTi) Department of Computational Engineering Federal University of Maranhão (UFMA) Maranhão São Luís Brazil Department of Chemical Engineering Federal University of Maranhão (UFMA) Maranhão São Luís Brazil Processes and Thermal Systems Laboratory (LPSisTer) Department of Mechanical Engineering Federal University of Maranhão (UFMA) Maranhão São Luís Brazil
The production of biofuels to be used as bioenergy under combustion processes generates some gaseous emissions (CO, CO2, NOx, SOx, and other pollutants), affecting living organisms and requiring careful assessments. H... 详细信息
来源: 评论
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI  41
Position: Bayesian Deep Learning is Needed in the Age of Lar...
收藏 引用
41st International Conference on Machine Learning, ICML 2024
作者: Papamarkou, Theodore Skoularidou, Maria Palla, Konstantina Aitchison, Laurence Arbel, Julyan Dunson, David Filippone, Maurizio Fortuin, Vincent Hennig, Philipp Hernández-Lobato, José Miguel Hubin, Aliaksandr Immer, Alexander Karaletsos, Theofanis Khan, Mohammad Emtiyaz Kristiadi, Agustinus Li, Yingzhen Mandt, Stephan Nemeth, Christopher Osborne, Michael A. Rudner, Tim G.J. Rügamer, David Teh, Yee Whye Welling, Max Wilson, Andrew Gordon Zhang, Ruqi Department of Mathematics The University of Manchester Manchester United Kingdom Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge United States Spotify London United Kingdom Computational Neuroscience Unit University of Bristol Bristol United Kingdom Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University United States Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany Department of Computer Science Technical University of Munich Munich Germany Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge United Kingdom Department of Mathematics University of Oslo Oslo Norway Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative CA United States Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London United Kingdom Department of Computer Science UC Irvine Irvine United States Department of Mathematics and Statistics Lancaster University Lancaster United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Center for Data Science New York University New York United States Department of Statistics LMU Munich Munich Germany DeepMind London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences Center for Data Science Computer Science Department New York University New York United States Department of Computer Science Purdue University West Lafayette United States
In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective... 详细信息
来源: 评论
Thermal Conductivity of Water at Extreme Conditions
arXiv
收藏 引用
arXiv 2023年
作者: Zhang, Cunzhi Puligheddu, Marcello Zhang, Linfeng Car, Roberto Galli, Giulia Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States Materials Science Division Center for Molecular Engineering Argonne National Laboratory LemontIL60439 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Chemistry University of Chicago ChicagoIL60637 United States
Measuring the thermal conductivity (κ) of water at extreme conditions is a challenging task and few experimental data are available. We predict κ for temperatures and pressures relevant to the conditions of the Eart... 详细信息
来源: 评论
Liquid-liquid transition in water from first principles
arXiv
收藏 引用
arXiv 2022年
作者: Gartner, Thomas E. Piaggi, Pablo M. Car, Roberto Panagiotopoulos, Athanassios Z. Debenedetti, Pablo G. Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Chemical and Biological Engineering Princeton University PrincetonNJ08544 United States
A longstanding question in water research is the possibility that supercooled liquid water can undergo a liquid-liquid phase transition (LLT) into high- and low-density liquids. We used several complementary molecular... 详细信息
来源: 评论
mechanoChemML: A software library for machine learning in computational materials physics
arXiv
收藏 引用
arXiv 2021年
作者: Zhang, X. Teichert, G.H. Wang, Z. Duschenes, M. Srivastava, Siddhartha Livingston, E. Holber, J. Shojaei, M. Faghih Sundararajan, A. Garikipati, K. Department of Mechanical Engineering University of Michigan United States Applied Physics Program University of Michigan United States Department of Mathematics University of Michigan United States Michigan Institute for Computational Discovery & Engineering University of Michigan United States
We present mechanoChemML, a machine learning software library for computational materials physics. mechanoChemML is designed to function as an interface between platforms that are widely used for machine learning on o... 详细信息
来源: 评论
Structural Properties of Hyperuniform Networks
arXiv
收藏 引用
arXiv 2024年
作者: Newby, Eli Shi, Wenlong Jiao, Yang Albert, Reka Torquato, Salvatore Department of Physics Pennsylvania State University University ParkPA16802 United States Materials Science and Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Institute of Materials Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States
Disordered hyperuniform many-particle systems are recently discovered exotic states of matter, characterized by a complete suppression of normalized infinite-wavelength density fluctuations, as in perfect crystals, an... 详细信息
来源: 评论
Periodicity Scoring of Time Series Encodes Dynamical Behavior of the Tumor Suppressor p53 ⁎ ⁎
收藏 引用
IFAC-PapersOnLine 2021年 第9期54卷 488-495页
作者: Caroline Moosmüller Christopher J. Tralie Mahdi Kooshkbaghi Zehor Belkhatir Maryam Pouryahya José Reyes Joseph O. Deasy Allen R. Tannenbaum Ioannis G. Kevrekidis C. Moosmüller and C. Tralie contributed equally to this work Department of Mathematics University of California San Diego La Jolla CA 92093 USA Department of Medical Physics Memorial Sloan-Kettering Cancer Center NY USA Department of Chemical and Biomolecular Engineering Johns Hopkins University Baltimore MD 21218 USA Department of Mathematics and Computer Science Ursinus College Collegeville PA USA Program in Applied and Computational Mathematics Princeton University NJ USA School of Engineering and Sustainable Development De Montfort University Leicester UK Cancer Biology and Genetics Program and Computational and Systems Biology Program Memorial Sloan-Kettering Cancer Center New York NY 10065 USA and Department of Systems Biology Harvard Medical School Boston MA 02115 USA Departments of Computer Science and Applied Mathematics & Statistics Stony Brook University NY USA
In this paper we analyze the dynamical behavior of the tumor suppressor protein p53, an essential player in the cellular stress response, which prevents a cell from dividing if severe DNA damage is present. When this ... 详细信息
来源: 评论
Local number fluctuations in ordered and disordered phases of water across temperatures: Higher-order moments and degrees of tetrahedrality
arXiv
收藏 引用
arXiv 2024年
作者: Klatt, Michael A. Kim, Jaeuk Gartner, Thomas E. Torquato, Salvatore Institute for AI Safety and Security Wilhelm-Runge-Str. 10 Ulm89081 Germany Institute for Material Physics in Space Köln51170 Germany Department of Physics Ludwig-Maximilians-Universität München Schellingstr. 4 Munich80799 Germany Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Materials Institute Princeton University PrincetonNJ08544 United States Department of Chemical & Biomolecular Engineering Lehigh University BethlehemPA18015 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States
The isothermal compressibility (i.e., the asymptotic number variance) of equilibrium liquid water as a function of temperature is minimal near ambient conditions. This anomalous non-monotonic temperature dependence is... 详细信息
来源: 评论
Biwhitening reveals the rank of a count matrix
arXiv
收藏 引用
arXiv 2021年
作者: Landa, Boris Zhang, Thomas T.C.K. Kluger, Yuval Program in Applied Mathematics Yale University United States Department of Electrical and Systems Engineering University of Pennsylvania United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University United States Department of Pathology Yale University School of Medicine United States
Estimating the rank of a corrupted data matrix is an important task in data analysis, most notably for choosing the number of components in PCA. Significant progress on this task was achieved using random matrix theor... 详细信息
来源: 评论