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ORCIDLinda R. Petzold
Linda Ruth Petzold
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- affiliation: University of California, Santa Barbara, USA
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2020 – today
- 2024
[j69]Colby Fronk
, Jaewoong Yun, Prashant Singh, Linda R. Petzold:
Bayesian polynomial neural networks and polynomial neural ordinary differential equations. PLoS Comput. Biol. 20(10): 1012414 (2024)- [j68]Yuqing Wang, Yun Zhao, Linda R. Petzold:
An empirical study on the robustness of the segment anything model (SAM). Pattern Recognit. 155: 110685 (2024) - [c34]Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda R. Petzold, William Yang Wang, Wei Cheng:
A Survey on Detection of LLMs-Generated Content. EMNLP (Findings) 2024: 9786-9805 - [c33]Xianjun Yang, Wei Cheng, Yue Wu, Linda Ruth Petzold, William Yang Wang, Haifeng Chen:
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text. ICLR 2024 - [c32]Xinlu Zhang, Shiyang Li, Xianjun Yang, Chenxin Tian, Yao Qin, Linda Ruth Petzold:
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting. ICLR 2024 - [i41]Xianjun Yang, Stephen D. Wilson, Linda R. Petzold:
Quokka: An Open-source Large Language Model ChatBot for Material Science. CoRR abs/2401.01089 (2024) - [i40]Zhiyu Zoey Chen, Jing Ma, Xinlu Zhang, Nan Hao, An Yan, Armineh Nourbakhsh, Xianjun Yang, Julian J. McAuley, Linda R. Petzold, William Yang Wang:
A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law. CoRR abs/2405.01769 (2024) - [i39]Xinlu Zhang, Zhiyu Zoey Chen, Xi Ye, Xianjun Yang, Lichang Chen, William Yang Wang, Linda Ruth Petzold:
Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning. CoRR abs/2405.20535 (2024) - [i38]Zekun Li, Xianjun Yang, Kyuri Choi, Wanrong Zhu, Ryan Hsieh, HyeonJung Kim, Jin Hyuk Lim, Sungyoung Ji, Byungju Lee, Xifeng Yan, Linda Ruth Petzold, Stephen D. Wilson, Woosang Lim, William Yang Wang:
MMSci: A Multimodal Multi-Discipline Dataset for PhD-Level Scientific Comprehension. CoRR abs/2407.04903 (2024) - [i37]Colby Fronk, Linda R. Petzold:
Training Stiff Neural Ordinary Differential Equations with Implicit Single-Step Methods. CoRR abs/2410.05592 (2024) - 2023
- [c31]Xianjun Yang, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Xiaoman Pan, Linda R. Petzold, Dong Yu:
OASum: Large-Scale Open Domain Aspect-based Summarization. ACL (Findings) 2023: 4381-4401 - [c30]Xianjun Yang, Yujie Lu, Linda R. Petzold:
Few-Shot Document-Level Event Argument Extraction. ACL (1) 2023: 8029-8046 - [c29]Xinlu Zhang, Shiyang Li, Zhiyu Chen, Xifeng Yan, Linda Ruth Petzold:
Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling. ICML 2023: 41300-41313 - [c28]Yuqing Wang, Yun Zhao, Linda R. Petzold:
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding. MLHC 2023: 804-823 - [i36]Xianjun Yang, Stephen D. Wilson, Linda R. Petzold:
MatKB: Semantic Search for Polycrystalline Materials Synthesis Procedures. CoRR abs/2302.05597 (2023) - [i35]Xianjun Yang, Wei Cheng, Xujiang Zhao, Linda R. Petzold, Haifeng Chen:
Dynamic Prompting: A Unified Framework for Prompt Tuning. CoRR abs/2303.02909 (2023) - [i34]Yuqing Wang, Yun Zhao, Linda R. Petzold:
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding. CoRR abs/2304.05368 (2023) - [i33]Yuqing Wang, Yun Zhao, Linda R. Petzold:
An Empirical Study on the Robustness of the Segment Anything Model (SAM). CoRR abs/2305.06422 (2023) - [i32]Xinlu Zhang, Shiyang Li, Xianjun Yang, Chenxin Tian, Yao Qin, Linda Ruth Petzold:
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting. CoRR abs/2305.12723 (2023) - [i31]Xianjun Yang, Wei Cheng, Linda R. Petzold, William Yang Wang, Haifeng Chen:
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text. CoRR abs/2305.17359 (2023) - [i30]Colby Fronk, Jaewoong Yun, Prashant Singh, Linda R. Petzold:
Bayesian polynomial neural networks and polynomial neural ordinary differential equations. CoRR abs/2308.10892 (2023) - [i29]Xianjun Yang, Xiao Wang, Qi Zhang, Linda R. Petzold, William Yang Wang, Xun Zhao, Dahua Lin:
Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models. CoRR abs/2310.02949 (2023) - [i28]Xianjun Yang, Kexun Zhang, Haifeng Chen, Linda R. Petzold, William Yang Wang, Wei Cheng:
Zero-Shot Detection of Machine-Generated Codes. CoRR abs/2310.05103 (2023) - [i27]Xinlu Zhang, Chenxin Tian, Xianjun Yang, Lichang Chen, Zekun Li, Linda Ruth Petzold:
AlpaCare: Instruction-tuned Large Language Models for Medical Application. CoRR abs/2310.14558 (2023) - [i26]Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda R. Petzold, William Yang Wang, Wei Cheng:
A Survey on Detection of LLMs-Generated Content. CoRR abs/2310.15654 (2023) - [i25]Xinlu Zhang, Yujie Lu, Weizhi Wang, An Yan, Jun Yan, Lianke Qin, Heng Wang, Xifeng Yan, William Yang Wang, Linda Ruth Petzold:
GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks. CoRR abs/2311.01361 (2023) - 2022
- [j67]Bilal Shaikh, Lucian P. Smith, Dan Vasilescu, Gnaneswara Marupilla, Michael Wilson, Eran Agmon, Henry Agnew, Steven S. Andrews, Azraf Anwar, Moritz E. Beber, Frank T. Bergmann, David Brooks, Lutz Brusch, Laurence Calzone, Kiri Choi, Joshua Cooper, John Detloff, Brian Drawert, Michel Dumontier, G. Bard Ermentrout, James R. Faeder, Andrew P. Freiburger, Fabian Fröhlich, Akira Funahashi, Alan Garny, John H. Gennari, Padraig Gleeson, Anne Goelzer, Zachary B. Haiman, Jan Hasenauer, Joseph L. Hellerstein, Henning Hermjakob, Stefan Hoops, Jon C. Ison, Diego Jahn, Henry V. Jakubowski, Ryann Jordan, Matús Kalas, Matthias König, Wolfram Liebermeister, Rahuman S. Malik-Sheriff, Synchon Mandal, Robert A. McDougal, J. Kyle Medley, Pedro Mendes, Robert Müller, Chris J. Myers, Aurélien Naldi, Tung V. N. Nguyen, David P. Nickerson, Brett G. Olivier, Drashti Patoliya, Loïc Paulevé, Linda R. Petzold, Ankita Priya, Anand K. Rampadarath, Johann M. Rohwer, Ali Sinan Saglam, Dilawar Singh, Ankur Sinha, Jacky L. Snoep, Hugh Sorby, Ryan K. Spangler, Jörn Starruß, Payton J. Thomas, David D. van Niekerk, Daniel Weindl, Fengkai Zhang, Anna Zhukova, Arthur P. Goldberg, James C. Schaff, Michael L. Blinov, Herbert M. Sauro, Ion I. Moraru, Jonathan R. Karr:
BioSimulators: a central registry of simulation engines and services for recommending specific tools. Nucleic Acids Res. 50(W1): 108-114 (2022) - [j66]Richard M. Jiang, Prashant Singh, Fredrik Wrede, Andreas Hellander, Linda R. Petzold:
Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods. PLoS Comput. Biol. 18(1) (2022) - [c27]Yuqing Wang, Yun Zhao, Linda R. Petzold:
Predicting the need for blood transfusion in intensive care units with reinforcement learning. BCB 2022: 7:1-7:10 - [c26]Xianjun Yang, Ya Zhuo, Julia Zuo, Xinlu Zhang, Stephen D. Wilson, Linda R. Petzold:
PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text. EMNLP (Findings) 2022: 6033-6046 - [c25]Haotian Xia, Rhys Tracy, Yun Zhao, Erwan Fraisse, Yuan-Fang Wang, Linda R. Petzold:
VREN: Volleyball Rally Dataset with Expression Notation Language. ICKG 2022: 337-346 - [c24]Fredrik Wrede, Robin Eriksson, Richard M. Jiang, Linda R. Petzold, Stefan Engblom, Andreas Hellander, Prashant Singh:
Robust and integrative Bayesian neural networks for likelihood-free parameter inference. IJCNN 2022: 1-10 - [i24]Bilal Shaikh, Lucian P. Smith, Dan Vasilescu, Gnaneswara Marupilla, Michael Wilson, Eran Agmon, Henry Agnew, Steven S. Andrews, Azraf Anwar, Moritz E. Beber, Frank T. Bergmann, David Brooks, Lutz Brusch, Laurence Calzone, Kiri Choi, Joshua Cooper, John Detloff, Brian Drawert, Michel Dumontier, G. Bard Ermentrout, James R. Faeder, Andrew P. Freiburger, Fabian Fröhlich, Akira Funahashi, Alan Garny, John H. Gennari, Padraig Gleeson, Anne Goelzer, Zachary B. Haiman, Joseph L. Hellerstein, Stefan Hoops, Jon C. Ison, Diego Jahn, Henry V. Jakubowski, Ryann Jordan, Matús Kalas, Matthias König, Wolfram Liebermeister, Synchon Mandal, Robert A. McDougal, J. Kyle Medley, Pedro Mendes, Robert Müller, Chris J. Myers, Aurélien Naldi, Tung V. N. Nguyen, David P. Nickerson, Brett G. Olivier, Drashti Patoliya, Loïc Paulevé, Linda R. Petzold, Ankita Priya, Anand K. Rampadarath, Johann M. Rohwer, Ali Sinan Saglam, Dilawar Singh, Ankur Sinha, Jacky L. Snoep, Hugh Sorby, Ryan K. Spangler, Jörn Starruß, Payton J. Thomas, David D. van Niekerk, Daniel Weindl, Fengkai Zhang, Anna Zhukova, Arthur P. Goldberg, Michael L. Blinov, Herbert M. Sauro, Ion I. Moraru, Jonathan R. Karr:
BioSimulators: a central registry of simulation engines and services for recommending specific tools. CoRR abs/2203.06732 (2022) - [i23]Yuqing Wang, Yun Zhao, Rachael Callcut, Linda R. Petzold:
Integrating Physiological Time Series and Clinical Notes with Transformer for Early Prediction of Sepsis. CoRR abs/2203.14469 (2022) - [i22]Yuqing Wang, Yun Zhao, Linda R. Petzold:
Enhancing Transformer Efficiency for Multivariate Time Series Classification. CoRR abs/2203.14472 (2022) - [i21]Yuqing Wang, Yun Zhao, Linda R. Petzold:
Predicting the Need for Blood Transfusion in Intensive Care Units with Reinforcement Learning. CoRR abs/2206.14198 (2022) - [i20]Colby Fronk, Linda R. Petzold:
Interpretable Polynomial Neural Ordinary Differential Equations. CoRR abs/2208.05072 (2022) - [i19]Xianjun Yang, Yujie Lu, Linda R. Petzold:
Few-Shot Document-Level Event Argument Extraction. CoRR abs/2209.02203 (2022) - [i18]Haotian Xia, Rhys Tracy, Yun Zhao, Erwan Fraisse, Yuan-Fang Wang, Linda R. Petzold:
VREN: Volleyball Rally Dataset with Expression Notation Language. CoRR abs/2209.13846 (2022) - [i17]Xinlu Zhang, Shiyang Li, Zhiyu Chen, Xifeng Yan, Linda R. Petzold:
Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling. CoRR abs/2210.12156 (2022) - [i16]Xianjun Yang, Ya Zhuo, Julia Zuo, Xinlu Zhang, Stephen D. Wilson, Linda R. Petzold:
PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text. CoRR abs/2210.12401 (2022) - [i15]Xianjun Yang, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Xiaoman Pan, Linda R. Petzold, Dong Yu:
OASum: Large-Scale Open Domain Aspect-based Summarization. CoRR abs/2212.09233 (2022) - 2021
- [j65]Richard M. Jiang, Bruno Jacob, Matthew Geiger, Sean Matthew, Bryan Rumsey, Prashant Singh, Fredrik Wrede, Tau-Mu Yi, Brian Drawert, Andreas Hellander, Linda R. Petzold:
Epidemiological modeling in StochSS Live! Bioinform. 37(17): 2787-2788 (2021) - [j64]Richard M. Jiang, Arya A. Pourzanjani, Mitchell J. Cohen, Linda R. Petzold:
Associations of longitudinal D-Dimer and Factor II on early trauma survival risk. BMC Bioinform. 22(1): 122 (2021) - [j63]Richard M. Jiang, Fredrik Wrede, Prashant Singh, Andreas Hellander, Linda R. Petzold:
Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators. BMC Bioinform. 22(1): 339 (2021) - [j62]Samhita P. Banavar, Michael Trogdon, Brian Drawert, Tau-Mu Yi, Linda R. Petzold, Otger Campàs:
Coordinating cell polarization and morphogenesis through mechanical feedback. PLoS Comput. Biol. 17(1) (2021) - [c23]Xinlu Zhang, Shiyang Liy, Zhuowei Cheng, Rachael Callcut, Linda R. Petzold:
Domain Adaptation for Trauma Mortality Prediction in EHRs with Feature Disparity. BIBM 2021: 1145-1152 - [c22]Xianjun Yang, Xinlu Zhang, Julia Zuo, Stephen D. Wilson, Linda R. Petzold:
An Analysis of Relation Extraction within Sentences from Wet Lab Protocols. IEEE BigData 2021: 562-570 - [c21]Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda R. Petzold:
Empirical Quantitative Analysis of COVID-19 Forecasting Models. ICDM (Workshops) 2021: 517-526 - [i14]Fredrik Wrede, Robin Eriksson, Richard M. Jiang, Linda R. Petzold, Stefan Engblom, Andreas Hellander, Prashant Singh:
Robust and integrative Bayesian neural networks for likelihood-free parameter inference. CoRR abs/2102.06521 (2021) - [i13]Yun Zhao, Qinghang Hong, Xinlu Zhang, Yu Deng, Yuqing Wang, Linda R. Petzold:
BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients. CoRR abs/2103.10928 (2021) - [i12]Yuqing Wang, Yun Zhao, Rachael Callcut, Linda R. Petzold:
Empirical Analysis of Machine Learning Configurations for Prediction of Multiple Organ Failure in Trauma Patients. CoRR abs/2103.10929 (2021) - [i11]Xinlu Zhang, Yun Zhao, Rachael Callcut, Linda R. Petzold:
Multiple Organ Failure Prediction with Classifier-Guided Generative Adversarial Imputation Networks. CoRR abs/2106.11878 (2021) - [i10]Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda R. Petzold:
Empirical Quantitative Analysis of COVID-19 Forecasting Models. CoRR abs/2110.00174 (2021) - 2020
- [j61]Hamed O. Ghaffari, Samuel C. Grant, Linda R. Petzold, Michael G. Harrington:
Regulation of CSF and Brain Tissue Sodium Levels by the Blood-CSF and Blood-Brain Barriers During Migraine. Frontiers Comput. Neurosci. 14: 4 (2020) - [c20]Yun Zhao, Franklin Ly, Qinghang Hong, Zhuowei Cheng, Tyler Santander, Henry T. Yang, Paul K. Hansma, Linda R. Petzold:
How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment. ICDM (Workshops) 2020: 651-660 - [i9]James Bird, Linda R. Petzold, Philip Lubin, Dulia Deacon:
Advances in Deep Space Exploration via Simulators & Deep Learning. CoRR abs/2002.04051 (2020) - [i8]Yun Zhao, Richard M. Jiang, Zhenni Xu, Elmer Guzman, Paul K. Hansma, Linda R. Petzold:
Scalable Bayesian Functional Connectivity Inference for Multi-Electrode Array Recordings. CoRR abs/2007.02198 (2020) - [i7]Yun Zhao, Franklin Ly, Qinghang Hong, Zhuowei Cheng, Tyler Santander, Henry T. Yang, Paul K. Hansma, Linda R. Petzold:
How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment. CoRR abs/2009.12202 (2020) - [i6]James Bird, Kellan Colburn, Linda R. Petzold, Philip Lubin:
Model Optimization for Deep Space Exploration via Simulators and Deep Learning. CoRR abs/2012.14092 (2020)
2010 – 2019
- 2019
- [j60]Brian Drawert, Bruno Jacob, Zhen Li, Tau-Mu Yi, Linda R. Petzold:
A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems. J. Comput. Phys. 378: 1-17 (2019) - [j59]Brian A. Mitchell, Nina Lauharatanahirun, Javier O. Garcia, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Vettel, Linda R. Petzold:
A Minimum Free Energy Model of Motor Learning. Neural Comput. 31(10): 1945-1963 (2019) - [j58]Mark S. Alber, Adrian Buganza Tepole, William R. Cannon, Suvranu De, Salvador Dura-Bernal, Krishna C. Garikipati, George E. Karniadakis, William W. Lytton, Paris Perdikaris, Linda R. Petzold, Ellen Kuhl:
Integrating machine learning and multiscale modeling - perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. npj Digit. Medicine 2 (2019) - [c19]Yun Zhao, Elmer Guzman, Morgane Audouard, Zhuowei Cheng, Paul K. Hansma, Kenneth S. Kosik, Linda R. Petzold:
A Deep Learning Framework for Classification of in vitro Multi-Electrode Array Recordings. ICDM (Posters) 2019: 197-210 - [i5]Yun Zhao, Elmer Guzman, Morgane Audouard, Zhuowei Cheng, Paul K. Hansma, Kenneth S. Kosik, Linda R. Petzold:
A Deep Learning Framework for Classification of in vitro Multi-Electrode Array Recordings. CoRR abs/1906.02241 (2019) - 2018
- [j57]Abolfazl Doostparast Torshizi, Linda R. Petzold:
Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification. J. Am. Medical Informatics Assoc. 25(1): 99-108 (2018) - [j56]Samhita P. Banavar, Carlos Gomez, Michael Trogdon, Linda R. Petzold, Tau-Mu Yi, Otger Campàs:
Mechanical feedback coordinates cell wall expansion and assembly in yeast mating morphogenesis. PLoS Comput. Biol. 14(1) (2018) - [j55]Michael Trogdon, Brian Drawert, Carlos Gomez, Samhita P. Banavar, Tau-Mu Yi, Otger Campàs, Linda R. Petzold:
The effect of cell geometry on polarization in budding yeast. PLoS Comput. Biol. 14(6) (2018) - [j54]Abolfazl Doostparast Torshizi, Linda R. Petzold:
Sparse Pathway-Induced Dynamic Network Biomarker Discovery for Early Warning Signal Detection in Complex Diseases. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 1028-1034 (2018) - [c18]Mahnaz Koupaee, Yuanyang Zhang, Tie Bo Wu, Mitchell J. Cohen, Linda R. Petzold:
Identification of Disease States for Trauma Patients using Commonly Available Hospital Data. ICCABS 2018: 1-4 - 2017
- [j53]Abolfazl Doostparast Torshizi, Linda R. Petzold, Mitchell J. Cohen:
Multivariate soft repulsive system identification for constructing rule-based classification systems: Application to trauma clinical data. Neurocomputing 245: 77-85 (2017) - [c17]Yuanyang Zhang, Richard M. Jiang, Linda R. Petzold:
Survival Topic Models for Predicting Outcomes for Trauma Patients. ICDE 2017: 1497-1504 - [c16]Arya A. Pourzanjani, Tie Bo Wu, Richard M. Jiang, Mitchell J. Cohen, Linda R. Petzold:
Understanding Coagulopathy using Multi-view Data in the Presence of Sub-Cohorts: A Hierarchical Subspace Approach. MLHC 2017: 338-351 - 2016
- [j52]Rone Kwei Lim, J. William Pro, Matthew R. Begley, Marcel Utz, Linda R. Petzold:
High-performance simulation of fracture in idealized 'brick and mortar' composites using adaptive Monte Carlo minimization on the GPU. Int. J. High Perform. Comput. Appl. 30(2): 186-199 (2016) - [j51]Yuanyang Zhang, Tie Bo Wu, Bernie J. Daigle Jr., Mitchell J. Cohen, Linda R. Petzold:
Identification of disease states associated with coagulopathy in trauma. BMC Medical Informatics Decis. Mak. 16: 124 (2016) - [j50]Mahdi Golkaram, Stefan Hellander, Brian Drawert, Linda R. Petzold:
Macromolecular Crowding Regulates the Gene Expression Profile by Limiting Diffusion. PLoS Comput. Biol. 12(11) (2016) - [j49]Brian Drawert, Andreas Hellander, Benjamin B. Bales, Debjani Banerjee, Giovanni Bellesia, Bernie J. Daigle Jr., Geoffrey Douglas, Mengyuan Gu, Anand Gupta, Stefan Hellander, Christopher B. Horuk, Dibyendu Nath, Aviral Takkar, Sheng Wu, Per Lötstedt, Chandra Krintz, Linda R. Petzold:
Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist. PLoS Comput. Biol. 12(12) (2016) - [j48]Brian Drawert, Michael Trogdon, Salman Zubair Toor, Linda R. Petzold, Andreas Hellander:
MOLNs: A Cloud Platform for Interactive, Reproducible, and Scalable Spatial Stochastic Computational Experiments in Systems Biology Using PyURDME. SIAM J. Sci. Comput. 38(3) (2016) - [c15]Rone Kwei Lim, Linda R. Petzold, Çetin Kaya Koç:
Bitsliced High-Performance AES-ECB on GPUs. The New Codebreakers 2016: 125-133 - [c14]Kasturi Bhattacharjee, Linda R. Petzold:
What Drives Consumer Choices? Mining Aspects and Opinions on Large Scale Review Data Using Distributed Representation of Words. ICDM Workshops 2016: 908-915 - [i4]Brian A. Mitchell, Linda R. Petzold:
Multi-View Treelet Transform. CoRR abs/1606.00800 (2016) - [i3]Ulrich Rüde, Karen Willcox, Lois Curfman McInnes, Hans De Sterck, George Biros, Hans-Joachim Bungartz, James Corones, Evin Cramer, James Crowley, Omar Ghattas, Max D. Gunzburger, Michael Hanke, Robert J. Harrison, Michael A. Heroux, Jan S. Hesthaven, Peter K. Jimack, Chris Johnson, Kirk E. Jordan, David E. Keyes, Rolf H. Krause, Vipin Kumar, Stefan Mayer, Juan Meza, Knut Martin Mørken, J. Tinsley Oden, Linda R. Petzold, Padma Raghavan, Suzanne M. Shontz, Anne E. Trefethen, Peter R. Turner, Vladimir V. Voevodin, Barbara I. Wohlmuth, Carol S. Woodward:
Research and Education in Computational Science and Engineering. CoRR abs/1610.02608 (2016) - 2015
- [j47]Bernie J. Daigle Jr., Mohammad Soltani, Linda R. Petzold, Abhyudai Singh:
Inferring single-cell gene expression mechanisms using stochastic simulation. Bioinform. 31(9): 1428-1435 (2015) - [c13]Abolfazl Doostparast Torshizi, Linda R. Petzold, Mitchell J. Cohen:
Direct higher order fuzzy rule-based classification system: Application in mortality prediction. BIBM 2015: 846-852 - [c12]Yuanyang Zhang, Bernie J. Daigle Jr., Mitchell J. Cohen, Linda R. Petzold:
A Cure Time Model for Joint Prediction of Outcome and Time-to-Outcome. ICDM 2015: 1117-1122 - [c11]Kasturi Bhattacharjee, Linda R. Petzold:
Detecting Opinions in a Temporally Evolving Conversation on Twitter. SocInfo 2015: 82-97 - [i2]Brian Drawert, Michael Trogdon, Salman Zubair Toor, Linda R. Petzold, Andreas Hellander:
MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME. CoRR abs/1508.03604 (2015) - 2014
- [j46]Andri Bezzola, Benjamin B. Bales, Richard C. Alkire, Linda R. Petzold:
An exact and efficient first passage time algorithm for reaction-diffusion processes on a 2D-lattice. J. Comput. Phys. 256: 183-197 (2014) - [j45]Andreas Hellander, Michael J. Lawson, Brian Drawert, Linda R. Petzold:
Local error estimates for adaptive simulation of the reaction-diffusion master equation via operator splitting. J. Comput. Phys. 266: 89-100 (2014) - [j44]Jin Fu, Sheng Wu, Hong Li, Linda R. Petzold:
The time dependent propensity function for acceleration of spatial stochastic simulation of reaction-diffusion systems. J. Comput. Phys. 274: 524-549 (2014) - [j43]Marc Griesemer, Carissa Young, Anne S. Robinson, Linda R. Petzold:
BiP Clustering Facilitates Protein Folding in the Endoplasmic Reticulum. PLoS Comput. Biol. 10(7) (2014) - [c10]Christopher B. Horuk, Geoffrey Douglas, Anand Gupta, Chandra Krintz, Benjamin B. Bales, Giovanni Bellesia, Brian Drawert, Rich Wolski, Linda R. Petzold, Andreas Hellander:
Automatic and portable cloud deployment for scientific simulations. HPCS 2014: 374-381 - [c9]Kasturi Bhattacharjee, Linda R. Petzold:
Probabilistic User-Level Opinion Detection on Online Social Networks. SocInfo 2014: 309-325 - 2013
- [j42]Ruoting Yang, Bernie J. Daigle Jr., Seid Y. Muhie, Rasha Hammamieh, Marti Jett, Linda R. Petzold, Francis J. Doyle III:
Core modular blood and brain biomarkers in social defeat mouse model for post traumatic stress disorder. BMC Syst. Biol. 7: 80 (2013) - [j41]Jin Fu, Sheng Wu, Linda R. Petzold:
Time dependent solution for acceleration of tau-leaping. J. Comput. Phys. 235: 446-457 (2013) - [j40]Michael J. Lawson, Brian Drawert, Mustafa Khammash, Linda R. Petzold, Tau-Mu Yi:
Spatial Stochastic Dynamics Enable Robust Cell Polarization. PLoS Comput. Biol. 9(7) (2013) - [c8]Kathy Macropol, Petko Bogdanov, Ambuj K. Singh, Linda R. Petzold, Xifeng Yan:
I act, therefore I judge: network sentiment dynamics based on user activity change. ASONAM 2013: 396-402 - [i1]Andreas Hellander, Michael J. Lawson, Brian Drawert, Linda R. Petzold:
Local error estimates for adaptive simulation of the Reaction-Diffusion Master Equation via operator splitting. CoRR abs/1305.3639 (2013) - 2012
- [j39]Ruoting Yang, Bernie J. Daigle Jr., Linda R. Petzold, Francis J. Doyle III:
Core module biomarker identification with network exploration for breast cancer metastasis. BMC Bioinform. 13: 12 (2012) - [j38]Bernie J. Daigle Jr., Min K. Roh, Linda R. Petzold, Jarad Niemi:
Accelerated maximum likelihood parameter estimation for stochastic biochemical systems. BMC Bioinform. 13: 68 (2012) - [j37]Chris Bunch, Brian Drawert, Navraj Chohan, Chandra Krintz, Linda R. Petzold, Khawaja S. Shams:
Language and Runtime Support for Automatic Configuration and Deployment of Scientific Computing Software over Cloud Fabrics. J. Grid Comput. 10(1): 23-46 (2012) - [c7]Per-Olov Östberg, Andreas Hellander, Brian Drawert, Erik Elmroth, Sverker Holmgren, Linda R. Petzold:
Abstractions for Scaling eScience Applications to Distributed Computing Environments - A StratUm Integration Case Study in Molecular Systems Biology. BIOINFORMATICS 2012: 290-294 - [c6]Per-Olov Östberg, Andreas Hellander, Brian Drawert, Erik Elmroth, Sverker Holmgren, Linda R. Petzold:
Reducing Complexity in Management of eScience Computations. CCGRID 2012: 845-852 - [c5]Linda R. Petzold, Chandra Krintz:
Stochastic Simulation Service: Towards an Integrated Development Environment for Modeling and Simulation of Stochastic Biochemical Systems. SC Companion 2012: 2303-2324 - 2011
- [j36]Kevin R. Sanft, Sheng Wu, Min K. Roh, Jin Fu, Rone Kwei Lim, Linda R. Petzold:
StochKit2: software for discrete stochastic simulation of biochemical systems with events. Bioinform. 27(17): 2457-2458 (2011) - [j35]