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2020 – today
- 2024
[c37]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML 2024- [c36]Archit Vasan, Ozan Gökdemir, Alexander Brace, Arvind Ramanathan, Thomas S. Brettin, Rick Stevens, Venkatram Vishwanath:
High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model. IPDPS (Workshops) 2024: 571-580 - [i19]Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar:
Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR abs/2401.11037 (2024) - 2023
- [j23]Bharat Kale
, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, Michael E. Papka:
ChemoGraph: Interactive Visual Exploration of the Chemical Space. Comput. Graph. Forum 42(3): 13-24 (2023) - [j22]Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, A. Sofia F. Oliveira, Clare Morris, Anthony T. Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, S. Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders S. Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai K. Sirumalla, Michael O'Connor, Frederick R. Manby, Anima Anandkumar, David J. Hardy, James C. Phillips, Abraham C. Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John D. McCalpin, Christopher J. Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John E. Stone, Daniel M. Zuckerman, Adrian J. Mulholland, Thomas F. Miller III, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro:
#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. Int. J. High Perform. Comput. Appl. 37(1): 28-44 (2023) - [j21]Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j20]Rajendra P. Joshi, Katherine J. Schultz, Jesse William Wilson, Agustin Kruel, Rohith Anand Varikoti, Chathuri J. Kombala, Daniel W. Kneller, Stephanie Galanie, Gwyndalyn Phillips, Qiu Zhang, Leighton Coates, Jyothi Parvathareddy, Surekha Surendranathan, Ying Kong, Austin Clyde, Arvind Ramanathan, Colleen B. Jonsson, Kristoffer R. Brandvold, Mowei Zhou, Martha S. Head, Andrey Kovalevsky, Neeraj Kumar:
AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. J. Chem. Inf. Model. 63(5): 1438-1453 (2023) - [j19]Michael W. Irvin, Arvind Ramanathan, Carlos F. Lopez:
Model certainty in cellular network-driven processes with missing data. PLoS Comput. Biol. 19(4) (2023) - [c35]Wei Chen, Yihui Ren, Ai Kagawa, Matthew R. Carbone, Samuel Yen-Chi Chen, Xiaohui Qu, Shinjae Yoo, Austin Clyde, Arvind Ramanathan, Rick L. Stevens, Hubertus Van Dam, Deyu Lu:
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. ICMLA 2023: 800-807 - [c34]Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens:
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. PASC 2023: 1:1-1:11 - [c33]Gautham Dharuman, Arvind Ramanathan:
Protein Generation via Genome-scale Language Models with Bio-physical Scoring. SC Workshops 2023: 95-101 - [c32]Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath:
Scalable Lead Prediction with Transformers using HPC resources. SC Workshops 2023: 123 - [c31]Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster:
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. SC Workshops 2023: 2140-2146 - [i18]Ismail Alkhouri, Sumit Kumar Jha, Andre Beckus, George K. Atia, Alvaro Velasquez, Rickard Ewetz, Arvind Ramanathan, Susmit Jha:
On the Robustness of AlphaFold: A COVID-19 Case Study. CoRR abs/2301.04093 (2023) - [i17]Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens:
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. CoRR abs/2304.03210 (2023) - [i16]Wei Chen, Yihui Ren, Ai Kagawa, Matthew R. Carbone, Samuel Yen-Chi Chen, Xiaohui Qu, Shinjae Yoo, Austin Clyde, Arvind Ramanathan, Rick L. Stevens, Hubertus Johannes Jacobus Van Dam, Deyu Lu:
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. CoRR abs/2308.01921 (2023) - [i15]Rafael Vescovi, Tobias Ginsburg, Kyle Hippe, Doga Ozgulbas, Casey Stone, Abraham Stroka, Rory Butler, Ben Blaiszik, Tom Brettin, Kyle Chard, Mark Hereld, Arvind Ramanathan, Rick Stevens, Aikaterini Vriza, Jie Xu, Qingteng Zhang, Ian T. Foster:
Towards a Modular Architecture for Science Factories. CoRR abs/2308.09793 (2023) - [i14]Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster:
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. CoRR abs/2308.13701 (2023) - [i13]Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - 2022
- [j18]Anda Trifan, Defne Gorgun, Michael Salim, Zongyi Li, Alexander Brace, Maxim Zvyagin, Heng Ma, Austin Clyde, David Clark, David J. Hardy, Tom Burnley, Lei Huang, John D. McCalpin, Murali Emani, Hyenseung Yoo, Junqi Yin, Aristeidis Tsaris, Vishal Subbiah, Tanveer Raza, Jessica Liu, Noah Trebesch, Geoffrey Wells, Venkatesh Mysore, Tom Gibbs, James C. Phillips, S. Chakra Chennubhotla, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, John E. Stone, Emad Tajkhorshid, Sarah A. Harris, Arvind Ramanathan:
Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action. Int. J. High Perform. Comput. Appl. 36(5-6): 603-623 (2022) - [j17]Austin Clyde, Stephanie Galanie, Daniel W. Kneller, Heng Ma, Yadu N. Babuji, Ben Blaiszik, Alexander Brace, Thomas S. Brettin, Kyle Chard, Ryan Chard, Leighton Coates, Ian T. Foster, Darin Hauner, Vilmos Kertesz, Neeraj Kumar, Hyungro Lee, Zhuozhao Li, André Merzky, Jurgen G. Schmidt, Li Tan, Mikhail Titov, Anda Trifan, Matteo Turilli, Hubertus Van Dam, Srinivas C. Chennubhotla, Shantenu Jha, Andrey Kovalevsky, Arvind Ramanathan, Martha S. Head, Rick Stevens:
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. J. Chem. Inf. Model. 62(1): 116-128 (2022) - [c30]Sumit Kumar Jha, Rickard Ewetz, Alvaro Velasquez, Arvind Ramanathan, Susmit Jha:
Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. AAAI 2022: 9567-9574 - [c29]Alexander Brace, Igor Yakushin, Heng Ma, Anda Trifan, Todd S. Munson, Ian T. Foster, Arvind Ramanathan, Hyungro Lee, Matteo Turilli, Shantenu Jha:
Coupling streaming AI and HPC ensembles to achieve 100-1000× faster biomolecular simulations. IPDPS 2022: 806-816 - [i12]Ryien Hosseini, Filippo Simini, Austin Clyde, Arvind Ramanathan:
Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks. CoRR abs/2211.02720 (2022) - 2021
- [j16]Lorenzo Casalino, Abigail C. Dommer, Zied Gaieb, Emília P. Barros, Terra Sztain, Surl-Hee Ahn, Anda Trifan, Alexander Brace, Anthony T. Bogetti, Austin Clyde, Heng Ma, Hyungro Lee, Matteo Turilli, Syma Khalid, Lillian T. Chong, Carlos Simmerling, David J. Hardy, Julio D. C. Maia, James C. Phillips, Thorsten Kurth, Abraham C. Stern, Lei Huang, John D. McCalpin, Mahidhar Tatineni, Tom Gibbs, John E. Stone, Shantenu Jha, Arvind Ramanathan, Rommie E. Amaro:
AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. Int. J. High Perform. Comput. Appl. 35(5) (2021) - [j15]Eunice Cho, Margarida Rosa, Ruhi Anjum, Saman Mehmood, Mariya Soban, Moniza Mujtaba, Khair Bux, Syed Tarique Moin, Mohammad Tanweer, Sarath Dantu, Alessandro Pandini, Junqi Yin, Heng Ma, Arvind Ramanathan, Barira Islam, Antonia S. J. S. Mey, Debsindhu Bhowmik, Shozeb M. Haider:
Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites. J. Chem. Inf. Model. 61(6): 3058-3073 (2021) - [j14]Jeremy Feinstein, Ganesh Sivaraman, Kurt Picel, Brian Peters, Álvaro Vázquez-Mayagoitia, Arvind Ramanathan, Margaret Macdonell, Ian T. Foster, Eugene Yan:
Uncertainty-Informed Deep Transfer Learning of Perfluoroalkyl and Polyfluoroalkyl Substance Toxicity. J. Chem. Inf. Model. 61(12): 5793-5803 (2021) - [c28]Aymen Al Saadi, Dario Alfè, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Alexander Brace, Thomas S. Brettin, Kyle Chard, Ryan Chard, Austin Clyde, Peter V. Coveney, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Dieter Kranzlmüller, Thorsten Kurth, Hyungro Lee, Zhuozhao Li, Heng Ma, Gerald Mathias, André Merzky, Alexander Partin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Anda Trifan, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling, Junqi Yin:
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP 2021: 40:1-40:12 - [c27]Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash:
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD 2021: 4104-4105 - [c26]Akash Parvatikar, Om Choudhary, Arvind Ramanathan, Rebekah Jenkins, Olga Navolotskaia, Gloria Carter, Akif Burak Tosun, Jeffrey L. Fine, S. Chakra Chennubhotla:
Prototypical Models for Classifying High-Risk Atypical Breast Lesions. MICCAI (8) 2021: 143-152 - [c25]Hyungro Lee, André Merzky, Li Tan, Mikhail Titov, Matteo Turilli, Dario Alfè, Agastya Bhati, Alex Brace, Austin Clyde, Peter V. Coveney, Heng Ma, Arvind Ramanathan, Rick Stevens, Anda Trifan, Hubertus Van Dam, Shunzhou Wan, Sean R. Wilkinson, Shantenu Jha:
Scalable HPC & AI infrastructure for COVID-19 therapeutics. PASC 2021: 2:1-2:13 - [c24]Alexander Brace, Michael Salim, Vishal Subbiah, Heng Ma, Murali Emani, Anda Trifan, Austin R. Clyde, Corey Adams, Thomas D. Uram, Hyun Seung Yoo, Andew Hock, Jessica Liu, Venkatram Vishwanath, Arvind Ramanathan:
Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. PASC 2021: 6:1-6:13 - [c23]Arvind Ramanathan, Sumit Kumar Jha:
Adversarial Attacks against AI-driven Experimental Peptide Design Workflows. XLOOP@SC 2021: 30-35 - [i11]Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Austin R. Clyde, Mathis Bode, Li Tan, Mikhail Titov, André Merzky, Matteo Turilli, Shantenu Jha, Roger R. Highfield, Walter Rocchia, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney:
Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. CoRR abs/2103.02843 (2021) - [i10]Austin Clyde, Arvind Ramanathan, Rick Stevens:
Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds. CoRR abs/2103.06867 (2021) - [i9]Alexander Brace, Hyungro Lee, Heng Ma, Anda Trifan, Matteo Turilli, Igor Yakushin, Todd S. Munson, Ian T. Foster, Shantenu Jha, Arvind Ramanathan:
Achieving 100X faster simulations of complex biological phenomena by coupling ML to HPC ensembles. CoRR abs/2104.04797 (2021) - [i8]Austin Clyde, Thomas S. Brettin, Alexander Partin, Hyun Seung Yoo, Yadu N. Babuji, Ben Blaiszik, André Merzky, Matteo Turilli, Shantenu Jha, Arvind Ramanathan, Rick Stevens:
Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening. CoRR abs/2106.07036 (2021) - [i7]Max Zvyagin, Thomas S. Brettin, Arvind Ramanathan, Sumit Kumar Jha:
CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning Models. CoRR abs/2108.12768 (2021) - [i6]Sumit Kumar Jha, Arvind Ramanathan, Rickard Ewetz, Alvaro Velasquez, Susmit Jha:
Protein Folding Neural Networks Are Not Robust. CoRR abs/2109.04460 (2021) - 2020
- [j13]Atanu Acharya, Rupesh Agarwal, Matthew B. Baker, Jérôme Baudry, Debsindhu Bhowmik, Swen Böhm, Kendall G. Byler, Sam Yen-Chi Chen, Leighton Coates, Connor J. Cooper, Omar Demerdash, Isabella Daidone, John D. Eblen, Sally R. Ellingson, Stefano Forli, Jens Glaser, James C. Gumbart, John Gunnels, Oscar R. Hernandez, Stephan Irle, Daniel W. Kneller, Andrey Kovalevsky, Jeffrey M. Larkin, Travis J. Lawrence, Scott LeGrand, Shih-Hsien Liu, Julie C. Mitchell, Gilchan Park, Jerry M. Parks, Anna Pavlova, Loukas Petridis, Duncan Poole, Line Pouchard, Arvind Ramanathan, David M. Rogers, Diogo Santos-Martins, Aaron Scheinberg, Ada Sedova, Yue Shen, Jeremy C. Smith, Micholas Dean Smith, Carlos Soto, Aristides Tsaris, Mathialakan Thavappiragasam, Andreas F. Tillack, Josh Vincent Vermaas, Van Quan Vuong, Junqi Yin, Shinjae Yoo, Mai Zahran, Laura Zanetti Polzi:
Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J. Chem. Inf. Model. 60(12): 5832-5852 (2020) - [j12]M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan:
Distributed Bayesian optimization of deep reinforcement learning algorithms. J. Parallel Distributed Comput. 139: 43-52 (2020) - [j11]Sunny Raj, Jodh S. Pannu, Steven Lawrence Fernandes, Arvind Ramanathan, Laura L. Pullum, Sumit Kumar Jha:
Attacking NIST biometric image software using nonlinear optimization. Pattern Recognit. Lett. 131: 79-84 (2020) - [c22]Akash Parvatikar, Om Choudhary, Arvind Ramanathan, Olga Navolotskaia, Gloria Carter, Akif Burak Tosun, Jeffrey L. Fine, S. Chakra Chennubhotla:
Modeling Histological Patterns for Differential Diagnosis of Atypical Breast Lesions. MICCAI (5) 2020: 550-560 - [i5]Yadu N. Babuji, Ben Blaiszik, Tom Brettin, Kyle Chard, Ryan Chard, Austin Clyde, Ian T. Foster, Zhi Hong, Shantenu Jha, Zhuozhao Li, Xuefeng Liu, Arvind Ramanathan, Yi Ren, Nicholaus Saint, Marcus Schwarting, Rick Stevens, Hubertus Van Dam, Rick Wagner:
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release. CoRR abs/2006.02431 (2020) - [i4]Aymen Al Saadi, Dario Alfè, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Thomas S. Brettin, Kyle Chard, Ryan Chard, Peter V. Coveney, Anda Trifan, Alex Brace, Austin Clyde, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Thorsten Kurth, Dieter Kranzlmüller, Hyungro Lee, Zhuozhao Li, Heng Ma, André Merzky, Gerald Mathias, Alexander Partin, Junqi Yin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling:
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR abs/2010.06574 (2020) - [i3]Hyungro Lee, André Merzky, Li Tan, Mikhail Titov, Matteo Turilli, Dario Alfè, Agastya Bhati, Alex Brace, Austin Clyde, Peter V. Coveney, Heng Ma, Arvind Ramanathan, Rick Stevens, Anda Trifan, Hubertus Van Dam, Shunzhou Wan, Sean R. Wilkinson, Shantenu Jha:
Scalable HPC and AI Infrastructure for COVID-19 Therapeutics. CoRR abs/2010.10517 (2020) - [i2]Arvind Ramanathan, Heng Ma, Akash Parvatikar, S. Chakra Chennubhotla:
Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins. CoRR abs/2012.00885 (2020)
2010 – 2019
- 2019
- [j10]Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle, Noah Schaefferkoetter, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Lynne Penberthy, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi, Arvind Ramanathan:
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019) - [j9]Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, B. Aditya Prakash:
Data-driven efficient network and surveillance-based immunization. Knowl. Inf. Syst. 61(3): 1667-1693 (2019) - [c21]Hong-Jun Yoon, John Gounley, Shang Gao, Mohammed M. Alawad, Arvind Ramanathan, Georgia D. Tourassi:
Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. BHI 2019: 1-4 - [c20]Junghoon Chae, Debsindhu Bhowmik, Heng Ma, Arvind Ramanathan, Chad A. Steed:
Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations. IEEE BigData 2019: 1759-1764 - [c19]Srikanth B. Yoginath, Md. Maksudul Alam, Arvind Ramanathan, Debsindhu Bhowmik, Nouamane Laanait, Kalyan S. Perumalla:
Towards Native Execution of Deep Learning on a Leadership-Class HPC System. IPDPS Workshops 2019: 941-950 - [c18]Heng Ma, Debsindhu Bhowmik, Hyungro Lee, Matteo Turilli, Michael T. Young, Shantenu Jha, Arvind Ramanathan:
Deep Generative Model Driven Protein Folding Simulations. PARCO 2019: 45-55 - [c17]Hyungro Lee, Matteo Turilli, Shantenu Jha, Debsindhu Bhowmik, Heng Ma, Arvind Ramanathan:
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding. DLS@SC 2019: 12-19 - [i1]Hyungro Lee, Heng Ma, Matteo Turilli, Debsindhu Bhowmik, Shantenu Jha, Arvind Ramanathan:
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding. CoRR abs/1909.07817 (2019) - 2018
- [j8]Debsindhu Bhowmik, Shang Gao, Michael T. Young, Arvind Ramanathan:
Deep clustering of protein folding simulations. BMC Bioinform. 19-S(18): 47-58 (2018) - [j7]John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, James Blair Christian, Arvind Ramanathan, Xiao-Cheng Wu, Paul A. Fearn, Georgia D. Tourassi:
Scalable deep text comprehension for Cancer surveillance on high-performance computing. BMC Bioinform. 19-S(18): 99-110 (2018) - [j6]Shang Gao, Michael T. Young, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Georgia D. Tourassi, Arvind Ramanathan:
Hierarchical attention networks for information extraction from cancer pathology reports. J. Am. Medical Informatics Assoc. 25(3): 321-330 (2018) - [c16]Hong-Jun Yoon, Arvind Ramanathan, Folami Alamudun, Georgia D. Tourassi:
Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer. IWBI 2018: 107181H - [c15]Shang Gao, Arvind Ramanathan, Georgia D. Tourassi:
Hierarchical Convolutional Attention Networks for Text Classification. Rep4NLP@ACL 2018: 11-23 - [c14]M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan:
HyperSpace: Distributed Bayesian Hyperparameter Optimization. SBAC-PAD 2018: 339-347 - 2017
- [c13]Sunny Raj, Sumit Kumar Jha, Arvind Ramanathan, Laura L. Pullum:
Testing autonomous cyber-physical systems using fuzzing features from convolutional neural networks: work-in-progress. EMSOFT Companion 2017: 1:1-1:2 - [c12]Sunny Raj, Laura Pullum, Arvind Ramanathan, Sumit Kumar Jha:
SATYA : Defending Against Adversarial Attacks Using Statistical Hypothesis Testing. FPS 2017: 277-292 - [c11]Arvind Ramanathan, Laura L. Pullum, Zubir Husein, Sunny Raj, Neslisah Torosdagli, Sumanta N. Pattanaik, Sumit Kumar Jha:
Adversarial attacks on computer vision algorithms using natural perturbations. IC3 2017: 1-6 - [c10]Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura L. Pullum, B. Aditya Prakash:
Data-Driven Immunization. ICDM 2017: 615-624 - 2016
- [j5]Özgür Özmen, James J. Nutaro, Laura L. Pullum, Arvind Ramanathan:
Analyzing the impact of modeling choices and assumptions in compartmental epidemiological models. Simul. 92(5): 459-472 (2016) - [c9]Sudharshan S. Vazhkudai, John Harney, Raghul Gunasekaran, Dale Stansberry, Seung-Hwan Lim, Tom Barron, Andrew Nash, Arvind Ramanathan:
Constellation: A science graph network for scalable data and knowledge discovery in extreme-scale scientific collaborations. IEEE BigData 2016: 3052-3061 - [c8]Arvind Ramanathan, Laura L. Pullum, Faraz Hussain, Dwaipayan Chakrabarty, Sumit Kumar Jha:
Integrating symbolic and statistical methods for testing intelligent systems: Applications to machine learning and computer vision. DATE 2016: 786-791 - [c7]Hong-Jun Yoon, Arvind Ramanathan, Georgia D. Tourassi:
Multi-task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports. INNS Conference on Big Data 2016: 195-204 - 2015
- [j4]Arvind Ramanathan, Laura L. Pullum, Tanner C. Hobson, Chad A. Steed, Shannon P. Quinn, Chakra S. Chennubhotla, Silvia Valkova:
ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics. BMC Bioinform. 16(S17): S4 (2015) - [c6]Kunal Malhotra, Tanner C. Hobson, Silvia Valkova, Laura L. Pullum, Arvind Ramanathan:
Sequential pattern mining of electronic healthcare reimbursement claims: Experiences and challenges in uncovering how patients are treated by physicians. IEEE BigData 2015: 2670-2679 - [c5]Paul Bogdan, Turbo Majumder, Arvind Ramanathan, Yuankun Xue:
NoC Architectures as Enablers of Biological Discovery for Personalized and Precision Medicine. NOCS 2015: 27:1-27:11 - 2014
- [c4]Faraz Hussain, Arvind Ramanathan, Laura L. Pullum, Sumit Kumar Jha:
EpiSpec: A formal specification language for parameterized agent-based models against epidemiological ground truth. ICCABS 2014: 1-6 - [c3]Laura L. Pullum, Arvind Ramanathan:
Oak Ridge Biosurveillance Toolkit: Scalable machine learning for public health surveillance. ICCABS 2014: 1 - 2013
- [j3]Pratul K. Agarwal, Scott S. Hampton, Jeffrey D. Poznanovic, Arvind Ramanathan, Sadaf R. Alam, Paul S. Crozier:
Performance modeling of microsecond scale biological molecular dynamics simulations on heterogeneous architectures. Concurr. Comput. Pract. Exp. 25(10): 1356-1375 (2013) - 2012
- [c2]Virginia M. Burger, Arvind Ramanathan, Andrej J. Savol, Christopher B. Stanley, Pratul K. Agarwal, Chakra S. Chennubhotla:
Quasi-Anharmonic Analysis Reveals Intermediate States in the Nuclear Co-Activator Receptor Binding Domain Ensemble. Pacific Symposium on Biocomputing 2012: 70-81 - 2011
- [j2]Andrej J. Savol, Virginia M. Burger, Pratul K. Agarwal, Arvind Ramanathan, Chakra S. Chennubhotla:
QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin. Bioinform. 27(13): 52-60 (2011) - 2010
- [j1]Arvind Ramanathan, Pratul K. Agarwal, Maria G. Kurnikova, Christopher James Langmead:
An Online Approach for Mining Collective Behaviors from Molecular Dynamics Simulations. J. Comput. Biol. 17(3): 309-324 (2010)
2000 – 2009
- 2009
- [c1]Arvind Ramanathan, Pratul K. Agarwal, Maria G. Kurnikova, Christopher James Langmead:
An Online Approach for Mining Collective Behaviors from Molecular Dynamics Simulations. RECOMB 2009: 138-154
Coauthor Index
Alex Brace
aka: Alexander Brace
aka: Alexander Brace
Thomas S. Brettin
aka: Tom Brettin
aka: Tom Brettin
Austin Clyde
aka: Austin R. Clyde
aka: Austin R. Clyde
Rick L. Stevens
aka: Rick Stevens
aka: Rick Stevens
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