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ORCIDSayan Ghosh
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. The links to all actual bibliographies of persons of the same or a similar name can be found below. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Other persons with the same name
- Sayan Ghosh 0001 — Jadavpur University, Kolkata, India
- Sayan Ghosh 0002 — Indian Institute of Technology (IIT) Kharagpur, India
- Sayan Ghosh 0003 — Georgia Institute of Technology, Atlanta, GA, USA
- Sayan Ghosh 0004 — University of Southern California, Playa Vista, CA, USA
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2020 – today
- 2025
[j12]Milan Jain
, Nicolas Bohm Agostini, Sayan Ghosh, Antonino Tumeo:
Analyzing inference workloads for spatiotemporal modeling. Future Gener. Comput. Syst. 163: 107513 (2025)- 2024
- [j11]Omer Subasi, Sayan Ghosh, Joseph B. Manzano, Bruce Palmer, Andrés Márquez:
Analysis and Benchmarking of feature reduction for classification under computational constraints. Mach. Learn. Sci. Technol. 5(2): 20501 (2024) - [c46]Aishwarya Sarkar, Sayan Ghosh, Nathan R. Tallent, Ali Jannesari:
MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs. CLUSTER 2024: 62-73 - [c45]Sayan Ghosh, Tejas Srinivasan, Swabha Swayamdipta:
Compare without Despair: Reliable Preference Evaluation with Generation Separability. EMNLP (Findings) 2024: 12787-12805 - [c44]Rohit Zambre, Sayan Ghosh:
Message from the TPC Chairs: HOTI 2024. HOTI 2024: ix - [c43]Yan Kang, Sayan Ghosh, Mahmut T. Kandemir, Andrés Márquez:
Impact of Write-Allocate Elimination on Fujitsu A64FX. HPC Asia Workshops 2024: 24-35 - [c42]Md Nahid Newaz, Sayan Ghosh, Joshua Suetterlein, Nathan R. Tallent, Md Atiqul Mollah, Ming Hua:
Graph Analytics on Jellyfish topology. IPDPS 2024: 839-851 - [i31]Sandipp Krishnan Ravi, Yigitcan Comlek, Wei Chen, Arjun Pathak, Vipul Gupta, Rajnikant Umretiya, Andrew Hoffman, Ghanshyam Pilania, Piyush Pandita, Sayan Ghosh, Nathaniel Mckeever, Liping Wang:
Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process. CoRR abs/2402.04146 (2024) - [i30]Nurani Rajagopal Rohan, Vigneswaran C, Sayan Ghosh, Kishore Rajendran, Gaurav A, V. Srinivasa Chakravarthy:
Deep Oscillatory Neural Network. CoRR abs/2405.03725 (2024) - [i29]Devichand Budagam, Ayush Kumar, Sayan Ghosh, Anuj Shrivastav, Azamat Zhanatuly Imanbayev, Iskander Rafailovich Akhmetov, Dmitrii I. Kaplun, Sergey Antonov, Artem Rychenkov, Gleb Cyganov, Aleksandr Sinitca:
Instance Segmentation and Teeth Classification in Panoramic X-rays. CoRR abs/2406.03747 (2024) - [i28]Sayan Ghosh, Tejas Srinivasan, Swabha Swayamdipta:
Compare without Despair: Reliable Preference Evaluation with Generation Separability. CoRR abs/2407.01878 (2024) - [i27]Yigitcan Comlek, Sandipp Krishnan Ravi, Piyush Pandita, Sayan Ghosh, Liping Wang, Wei Chen:
Heterogenous Multi-Source Data Fusion Through Input Mapping and Latent Variable Gaussian Process. CoRR abs/2407.11268 (2024) - 2023
- [j10]Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock:
Reconciling Security and Communication Efficiency in Federated Learning. IEEE Data Eng. Bull. 46(1): 67-78 (2023) - [c41]Sayan Ghosh, Rakesh R. Menon, Shashank Srivastava:
LaSQuE: Improved Zero-Shot Classification from Explanations Through Quantifier Modeling and Curriculum Learning. ACL (Findings) 2023: 7403-7419 - [c40]Yiyuan Li, Rakesh R. Menon, Sayan Ghosh, Shashank Srivastava:
Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models. EMNLP 2023: 573-591 - [c39]Kangda Wei, Sayan Ghosh, Rakesh R. Menon, Shashank Srivastava:
Leveraging Multiple Teachers for Test-Time Adaptation of Language-Guided Classifiers. EMNLP (Findings) 2023: 7068-7088 - [c38]Bingsheng Yao, Ishan Jindal, Lucian Popa, Yannis Katsis, Sayan Ghosh, Lihong He, Yuxuan Lu, Shashank Srivastava, Yunyao Li, James A. Hendler, Dakuo Wang:
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture. EMNLP (Findings) 2023: 11629-11643 - [c37]Sayan Ghosh, Raja Karmakar, Twinkle Chatterjee, Sandipan Ghosal:
Emotion Classification and Respective Sticker Mapping Using Convolutional Neural Networks. ICCCNT 2023: 1-7 - [i26]Sayan Ghosh, Karthik Prasad, Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Graham Cormode, Peter Vajda:
Pruning Compact ConvNets for Efficient Inference. CoRR abs/2301.04502 (2023) - [i25]Jessica Zhao, Sayan Ghosh, Akash Bharadwaj, Chih-Yao Ma:
When does the student surpass the teacher? Federated Semi-supervised Learning with Teacher-Student EMA. CoRR abs/2301.10114 (2023) - [i24]Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael G. Rabbat, Carole-Jean Wu, Ilya Mironov:
Green Federated Learning. CoRR abs/2303.14604 (2023) - [i23]Bingsheng Yao, Ishan Jindal, Lucian Popa, Yannis Katsis, Sayan Ghosh, Lihong He, Yuxuan Lu, Shashank Srivastava, James A. Hendler, Dakuo Wang:
Beyond Labels: Empowering Human with Natural Language Explanations through a Novel Active-Learning Architecture. CoRR abs/2305.12710 (2023) - [i22]Yiyuan Li, Rakesh R. Menon, Sayan Ghosh, Shashank Srivastava:
Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models. CoRR abs/2311.04659 (2023) - [i21]Kangda Wei, Sayan Ghosh, Rakesh R. Menon, Shashank Srivastava:
Leveraging Multiple Teachers for Test-Time Adaptation of Language-Guided Classifiers. CoRR abs/2311.07538 (2023) - 2022
- [j9]Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Liping Wang:
Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds. Entropy 24(9): 1291 (2022) - [j8]Sayan Ghosh, Ryan E. Grant, Min Si:
Special Issue on Hot Interconnects. IEEE Micro 42(2): 35-36 (2022) - [j7]Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman:
Towards scaling community detection on distributed-memory heterogeneous systems. Parallel Comput. 111: 102898 (2022) - [j6]Sayan Ghosh, Nathan R. Tallent, Mahantesh Halappanavar:
Characterizing Performance of Graph Neighborhood Communication Patterns. IEEE Trans. Parallel Distributed Syst. 33(4): 915-928 (2022) - [c36]Han-Yi Chou, Sayan Ghosh:
Batched Graph Community Detection on GPUs. PACT 2022: 172-184 - [c35]Yuwei Bao, Sayan Ghosh, Joyce Chai:
Learning to Mediate Disparities Towards Pragmatic Communication. ACL (1) 2022: 2829-2842 - [c34]Sayan Ghosh, Shashank Srivastava:
ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understanding. ACL (1) 2022: 3989-4004 - [c33]Rakesh R. Menon, Sayan Ghosh, Shashank Srivastava:
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations. ACL (1) 2022: 6523-6546 - [c32]Milan Jain, Sayan Ghosh, Sai Pushpak Nandanoori:
Workload characterization of a time-series prediction system for spatio-temporal data. CF 2022: 159-168 - [c31]Sayan Ghosh:
Improved Distributed-memory Triangle Counting by Exploiting the Graph Structure. HPEC 2022: 1-6 - [c30]Hyungro Lee, Milan Jain, Sayan Ghosh:
Sparse Deep Neural Network Inference Using Different Programming Models. HPEC 2022: 1-6 - [c29]Anirban Bandyopadhyay, Sayan Ghosh, Dipayan Biswas, Raju Surampudi Bapi, V. Srinivasa Chakravarthy:
A Phenomenological Deep Oscillatory Neural Network Model to Capture the Whole Brain Dynamics in Terms of BOLD Signal. ICONIP (2) 2022: 160-171 - [i20]Yuwei Bao, Sayan Ghosh, Joyce Chai:
Learning to Mediate Disparities Towards Pragmatic Communication. CoRR abs/2203.13685 (2022) - [i19]Rakesh R. Menon, Sayan Ghosh, Shashank Srivastava:
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations. CoRR abs/2204.07142 (2022) - [i18]Shubham Dutta, Sayan Ghosh, Satyaki Bhattacharya, Satyajit Saha:
Pulse Shape Simulation and Discrimination using Machine-Learning Techniques. CoRR abs/2206.15156 (2022) - [i17]Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock:
Reconciling Security and Communication Efficiency in Federated Learning. CoRR abs/2207.12779 (2022) - [i16]Adam Thelen, Xiaoge Zhang, Olga Fink, Yan Lu, Sayan Ghosh, Byeng D. Youn, Michael D. Todd, Sankaran Mahadevan, Chao Hu, Zhen Hu:
A Comprehensive Review of Digital Twin - Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives. CoRR abs/2208.12904 (2022) - [i15]Adam Thelen, Xiaoge Zhang, Olga Fink, Yan Lu, Sayan Ghosh, Byeng D. Youn, Michael D. Todd, Sankaran Mahadevan, Chao Hu, Zhen Hu:
A Comprehensive Review of Digital Twin - Part 1: Modeling and Twinning Enabling Technologies. CoRR abs/2208.14197 (2022) - [i14]Sayan Ghosh, Rakesh R. Menon, Shashank Srivastava:
LaSQuE: Improved Zero-Shot Classification from Explanations Through Quantifier Modeling and Curriculum Learning. CoRR abs/2212.09104 (2022) - 2021
- [j5]Seher Acer, Ariful Azad, Erik G. Boman, Aydin Buluç, Karen D. Devine, S. M. Ferdous, Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Ananth Kalyanaraman, Arif Khan, Marco Minutoli, Alex Pothen, Sivasankaran Rajamanickam, Oguz Selvitopi, Nathan R. Tallent, Antonino Tumeo:
EXAGRAPH: Graph and combinatorial methods for enabling exascale applications. Int. J. High Perform. Comput. Appl. 35(6): 553-571 (2021) - [j4]Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [j3]Yuhao Wang, Yi Gao, Yongming Liu, Sayan Ghosh, Waad Subber, Piyush Pandita, Liping Wang:
Bayesian-entropy gaussian process for constrained metamodeling. Reliab. Eng. Syst. Saf. 214: 107762 (2021) - [c28]Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem:
Data-based Discovery of Governing Equations. AAAI Spring Symposium: MLPS 2021 - [c27]Sayan Ghosh, Zheng Qi, Snigdha Chaturvedi, Shashank Srivastava:
How Helpful is Inverse Reinforcement Learning for Table-to-Text Generation? ACL/IJCNLP (2) 2021: 71-79 - [c26]Sayan Ghosh, Yanfei Guo, Pavan Balaji, Assefaw H. Gebremedhin:
RMACXX: An Efficient High-Level C++ Interface over MPI-3 RMA. CCGRID 2021: 143-155 - [c25]Mahantesh Halappanavar, Marco Minutoli, Sayan Ghosh:
Graph analytics in the exascale era. CF 2021: 209 - [c24]Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li, Junier Oliva, Shashank Srivastava, Snigdha Chaturvedi:
Adversarial Scrubbing of Demographic Information for Text Classification. EMNLP (1) 2021: 550-562 - [c23]Sayan Ghosh, Shashank Srivastava:
Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning. EMNLP (Findings) 2021: 1449-1462 - [c22]Sayan Ghosh, Clara Alsobrooks, Martin Rüfenacht, Anthony Skjellum, Purushotham V. Bangalore, Andrew Lumsdaine:
Towards Modern C++ Language Support for MPI. ExaMPI@SC 2021: 27-35 - [c21]Sayan Ghosh, Nathan R. Tallent, Marco Minutoli, Mahantesh Halappanavar, Ramesh Peri, Ananth Kalyanaraman:
Single-node partitioned-memory for huge graph analytics: cost and performance trade-offs. SC 2021: 55 - [i13]Sayan Ghosh, Govinda A. Padmanabha, Cheng Peng, Steven Atkinson, Valeria Andreoli, Piyush Pandita, Thomas Vandeputte, Nicholas Zabaras, Liping Wang:
Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning. CoRR abs/2108.10163 (2021) - [i12]Sayan Ghosh, Shashank Srivastava:
ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understanding. CoRR abs/2109.06838 (2021) - [i11]Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li, Junier B. Oliva, Shashank Srivastava, Snigdha Chaturvedi:
Adversarial Scrubbing of Demographic Information for Text Classification. CoRR abs/2109.08613 (2021) - [i10]Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov:
Opacus: User-Friendly Differential Privacy Library in PyTorch. CoRR abs/2109.12298 (2021) - [i9]Sayan Ghosh, Shashank Srivastava:
Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning. CoRR abs/2110.00842 (2021) - [i8]Yonatan Ashenafi, Piyush Pandita, Sayan Ghosh:
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design. CoRR abs/2112.10944 (2021) - 2020
- [c20]Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, Mohit Bansal:
PRover: Proof Generation for Interpretable Reasoning over Rules. EMNLP (1) 2020: 122-136 - [c19]Sayan Ghosh, Mahantesh Halappanavar:
TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure. HPEC 2020: 1-6 - [i7]Steven Atkinson, Sayan Ghosh, Natarajan Chennimalai-Kumar, Genghis Khan, Liping Wang:
Bayesian task embedding for few-shot Bayesian optimization. CoRR abs/2001.00637 (2020) - [i6]Sayan Ghosh, Piyush Pandita, Steven Atkinson, Waad Subber, Yiming Zhang, Natarajan Chennimalai-Kumar, Suryarghya Chakrabarti, Liping Wang:
Advances in Bayesian Probabilistic Modeling for Industrial Applications. CoRR abs/2003.11939 (2020) - [i5]Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Valeria Andreoli, Thomas Vandeputte, Liping Wang:
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes. CoRR abs/2008.02386 (2020) - [i4]Raphael Gautier, Piyush Pandita, Sayan Ghosh, Dimitri Mavris:
A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes. CoRR abs/2008.03534 (2020) - [i3]Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, Mohit Bansal:
PRover: Proof Generation for Interpretable Reasoning over Rules. CoRR abs/2010.02830 (2020) - [i2]Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger G. Ghanem:
Data-based Discovery of Governing Equations. CoRR abs/2012.06036 (2020)
2010 – 2019
- 2019
- [c18]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman:
Scaling and Quality of Modularity Optimization Methods for Graph Clustering. HPEC 2019: 1-6 - [c17]Sayan Ghosh, Mahantesh Halappanavar, Ananth Kalyanaraman, Arif Khan, Assefaw H. Gebremedhin:
Exploring MPI Communication Models for Graph Applications Using Graph Matching as a Case Study. IPDPS 2019: 761-770 - [c16]Sayan Ghosh, Jose Echevarria, Vineet Batra, Ankit Phogat:
Exploring color variations for vector graphics. SIGGRAPH Posters 2019: 10:1-10:2 - [i1]Sayan Ghosh, Jesper Kristensen, Yiming Zhang, Waad Subber, Liping Wang:
A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty. CoRR abs/1907.11739 (2019) - 2018
- [c15]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Assefaw H. Gebremedhin:
Scalable Distributed Memory Community Detection Using Vite. HPEC 2018: 1-7 - [c14]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Hao Lu, Daniel G. Chavarría-Miranda, Arif Khan, Assefaw Hadish Gebremedhin:
Distributed Louvain Algorithm for Graph Community Detection. IPDPS 2018: 885-895 - [c13]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Assefaw H. Gebremedhin:
MiniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems. PMBS@SC 2018: 51-56 - 2016
- [c12]Sayan Ghosh, Assefaw Hadish Gebremedhin:
Parallelization of Bin Packing on Multicore Systems. HiPC 2016: 311-320 - [c11]Sayan Ghosh, Jeff R. Hammond, Antonio J. Peña, Pavan Balaji, Assefaw Hadish Gebremedhin, Barbara M. Chapman:
One-Sided Interface for Matrix Operations Using MPI-3 RMA: A Case Study with Elemental. ICPP 2016: 185-194 - [c10]Sayan Ghosh, Ayananta Das, Dilip Kumar Pratihar:
A New Form of Fuzzy Reasoning Tool to Ensure Both Accuracy and Readability. SoCPaR 2016: 54-65 - 2014
- [j2]Sayan Ghosh, Terrence Liao, Henri Calandra, Barbara M. Chapman:
Performance of CPU/GPU compiler directives on ISO/TTI kernels. Computing 96(12): 1149-1162 (2014) - [c9]Jeff R. Hammond, Sayan Ghosh, Barbara M. Chapman:
Implementing OpenSHMEM Using MPI-3 One-Sided Communication. OpenSHMEM 2014: 44-58 - [c8]Naveen Namashivayam, Sayan Ghosh, Dounia Khaldi, Deepak Eachempati, Barbara M. Chapman:
Native Mode-Based Optimizations of Remote Memory Accesses in OpenSHMEM for Intel Xeon Phi. PGAS 2014: 12:1-12:11 - 2013
- [c7]Sayan Ghosh, Sunita Chandrasekaran, Barbara M. Chapman:
Statistical modeling of power/energy of scientific kernels on a multi-GPU system. IGCC 2013: 1-6 - [c6]Priyanka Ghosh, Jeff R. Hammond, Sayan Ghosh, Barbara M. Chapman:
Performance Analysis of the NWChem TCE for Different Communication Patterns. PMBS@SC 2013: 281-294 - 2012
- [c5]Sayan Ghosh, T. V. Sreenivas:
Automatic Speech Segmentation Using Probabilistic Latent Component Modeling. INTERSPEECH 2012: 2262-2265 - [c4]Sayan Ghosh, Terrence Liao, Henri Calandra, Barbara M. Chapman:
Experiences with OpenMP, PGI, HMPP and OpenACC Directives on ISO/TTI Kernels. SC Companion 2012: 691-700 - [c3]Sayan Ghosh, Sunita Chandrasekaran, Barbara M. Chapman:
Poster: Statistical Power and Energy Modeling of Multi-GPU Kernels. SC Companion 2012: 1516 - 2011
- [j1]Sayan Ghosh, Abhishek Halder, Manoranjan Sinha:
Micro air vehicle path planning in fuzzy quadtree framework. Appl. Soft Comput. 11(8): 4859-4865 (2011) - [c2]Sayan Ghosh, Barbara M. Chapman:
Programming Strategies for GPUs and their Power Consumption. PACT 2011: 218
2000 – 2009
- 2007
- [c1]Abhishek Halder, Sayan Ghosh, Manoranjan Sinha:
Fuzzy Quadtree Based Path Planner and Trajectory Smoother for a Low Cost Unmanned Aerial Vehicle. IICAI 2007: 763-778
Coauthor Index
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