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ORCIDSumanta Mukherjee
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2020 – today
- 2024
[i8]Chandramouli Kamanchi, Sumanta Mukherjee, Kameshwaran Sampath, Pankaj Dayama, Arindam Jati, Vijay Ekambaram, Dzung Phan:
Activations Through Extensions: A Framework To Boost Performance Of Neural Networks. CoRR abs/2408.03599 (2024)- [i7]Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi, Vijay Ekambaram, Arindam Jati, Pankaj Dayama:
Towards Unbiased Evaluation of Time-series Anomaly Detector. CoRR abs/2409.13053 (2024) - 2023
- [c6]Arindam Jati
, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting. KDD 2023: 891-900 - [c5]Giridhar Ganapavarapu, Sumanta Mukherjee, Natalia Martinez Gil, Kanthi K. Sarpatwar, Amaresh Rajasekharan, Amit Dhurandhar, Vijay Arya, Roman Vaculín:
AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases. KDD 2023: 5777-5778 - [i6]Vikas C. Raykar, Arindam Jati, Sumanta Mukherjee, Nupur Aggarwal, Kanthi K. Sarpatwar, Giridhar Ganapavarapu, Roman Vaculín:
TsSHAP: Robust model agnostic feature-based explainability for time series forecasting. CoRR abs/2303.12316 (2023) - [i5]Surya Shravan Kumar Sajja, Sumanta Mukherjee, Satyam Dwivedi:
Semi-supervised counterfactual explanations. CoRR abs/2303.12634 (2023) - 2022
- [c4]Sumanta Mukherjee, Arindam Jati, Kanthi K. Sarpatwar, Roman Vaculín:
Physics-based multiple time-series univariate forecasting. IEEE Big Data 2022: 1054-1059 - [i4]Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchy-guided Model Selection for Time Series Forecasting. CoRR abs/2211.15092 (2022) - 2021
- [c3]Shravan Sajja, Nupur Aggarwal, Sumanta Mukherjee, Kushagra Manglik, Satyam Dwivedi, Vikas Raykar:
Explainable AI based Interventions for Pre-season Decision Making in Fashion Retail. COMAD/CODS 2021: 281-289 - [c2]Sumanta Mukherjee, Krishnasuri Narayanam, Nupur Aggarwal, Digbalay Bose, Amith Singhee:
Robust resource demand estimation using hierarchical Bayesian model in a distributed service system. COMAD/CODS 2021: 350-358 - [i3]Anirban Ghatak, Sumanta Mukherjee:
Intersection Patterns in Optimal Binary (5, 3) Doubling Subspace Codes. CoRR abs/2105.01584 (2021) - 2020
- [c1]Vijay Ekambaram, Kushagra Manglik, Sumanta Mukherjee, Surya Shravan Kumar Sajja, Satyam Dwivedi, Vikas Raykar:
Attention based Multi-Modal New Product Sales Time-series Forecasting. KDD 2020: 3110-3118 - [i2]Shravan Sajja, Nupur Aggarwal, Sumanta Mukherjee, Kushagra Manglik, Satyam Dwivedi, Vikas Raykar:
Explainable AI based Interventions for Pre-season Decision Making in Fashion Retail. CoRR abs/2008.07376 (2020)
2010 – 2019
- 2019
- [i1]Joy Bose, Sumanta Mukherjee:
Semi-Supervised Method using Gaussian Random Fields for Boilerplate Removal in Web Browsers. CoRR abs/1911.02991 (2019) - 2018
- [j5]Narmada Sambaturu, Sumanta Mukherjee, Martín López-García, Carmen Molina-París, Gautam I. Menon, Nagasuma Chandra:
Role of genetic heterogeneity in determining the epidemiological severity of H1N1 influenza. PLoS Comput. Biol. 14(3) (2018) - 2016
- [j4]Sumanta Mukherjee, Chiranjib Bhattacharyya, Nagasuma Chandra:
HLaffy: estimating peptide affinities for Class-1 HLA molecules by learning position-specific pair potentials. Bioinform. 32(15): 2297-2305 (2016) - 2014
- [j3]Praveen Anand, Deepesh Nagarajan, Sumanta Mukherjee, Nagasuma R. Chandra:
PLIC: protein-ligand interaction clusters. Database J. Biol. Databases Curation 2014 (2014) - 2013
- [j2]Soma Ghosh, Priyanka Baloni, Sumanta Mukherjee, Praveen Anand, Nagasuma R. Chandra:
A multi-level multi-scale approach to study essential genes in Mycobacterium tuberculosis. BMC Syst. Biol. 7: 132 (2013) - [j1]Sumanta Mukherjee, Awanti Sambarey, Karyala Prashanthi, Nagasuma R. Chandra:
Current trends in modeling host-pathogen interactions. WIREs Data Mining Knowl. Discov. 3(2): 109-128 (2013)
Coauthor Index
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