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ORCIDSoma S. Dhavala
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2020 – today
- 2024
[j5]Snehanshu Saha
, Jyotirmoy Sarkar, Soma S. Dhavala, Preyank Mota, Santonu Sarkar:
quantile-Long Short Term Memory: A Robust, Time Series Anomaly Detection Method. IEEE Trans. Artif. Intell. 5(8): 3939-3950 (2024)- 2023
- [i10]Snehanshu Saha, Jyotirmoy Sarkar, Soma S. Dhavala, Santonu Sarkar, Preyank Mota:
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data. CoRR abs/2302.08712 (2023) - [i9]Pronoma Banerjee, Manasi V. Gude, Rajvi J. Sampat, Sharvari M. Hedaoo, Soma S. Dhavala, Snehanshu Saha:
Correcting Model Misspecification via Generative Adversarial Networks. CoRR abs/2304.03805 (2023) - [i8]Aditya Challa, Snehanshu Saha, Soma S. Dhavala:
Decoupling Quantile Representations from Loss Functions. CoRR abs/2304.12766 (2023) - 2022
- [j4]Anuj Tambwekar, Anirudh Maiya, Soma S. Dhavala, Snehanshu Saha:
Estimation and Applications of Quantiles in Deep Binary Classification. IEEE Trans. Artif. Intell. 3(2): 275-286 (2022) - [j3]Tejas Prashanth, Snehanshu Saha, Sumedh Basarkod, Suraj Aralihalli, Soma S. Dhavala, Sriparna Saha, Raviprasad Aduri:
LipGene: Lipschitz Continuity Guided Adaptive Learning Rates for Fast Convergence on Microarray Expression Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3553-3563 (2022) - [j2]Rohan Mohapatra, Snehanshu Saha, Carlos A. Coello Coello, Anwesh Bhattacharya, Soma S. Dhavala, Sriparna Saha:
AdaSwarm: Augmenting Gradient-Based Optimizers in Deep Learning With Swarm Intelligence. IEEE Trans. Emerg. Top. Comput. Intell. 6(2): 329-340 (2022) - [c4]Omatharv Bharat Vaidya, Rithvik Terence DSouza, Soma S. Dhavala, Snehanshu Saha, Swagatam Das:
HMC-PSO: A Hamiltonian Monte Carlo and Particle Swarm Optimization-Based Optimizer. ICONIP (1) 2022: 212-223 - [i7]Aryaman Jeendgar, Aditya Pola, Soma S. Dhavala, Snehanshu Saha:
LogGENE: A smooth alternative to check loss for Deep Healthcare Inference Tasks. CoRR abs/2206.09333 (2022) - [i6]Omatharv Bharat Vaidya, Rithvik Terence DSouza, Snehanshu Saha, Soma S. Dhavala, Swagatam Das:
Hamiltonian Monte Carlo Particle Swarm Optimizer. CoRR abs/2206.14134 (2022) - 2021
- [c3]Shakkeel Ahmed, Prakash Bisht, Ravi S. Mula, Soma S. Dhavala:
A Deep Learning framework for Interoperable Machine Learning. AIMLSystems 2021: 23:1-23:7 - [i5]Anuj Tambwekar, Anirudh Maiya, Soma S. Dhavala, Snehanshu Saha:
Estimation and Applications of Quantiles in Deep Binary Classification. CoRR abs/2102.06575 (2021) - 2020
- [c2]Soma S. Dhavala, Chirag Bhatia, Joy Bose, Keyur Faldu, Aditi Avasthi:
Auto generation of diagnostic assessments and their quality evaluation. EDM 2020 - [c1]Snehanshu Saha, Tejas Prashanth, Suraj Aralihalli, Sumedh Basarkod, T. S. B. Sudarshan, Soma S. Dhavala:
LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks. IJCNN 2020: 1-8 - [i4]Shakkeel Ahmed, Ravi S. Mula, Soma S. Dhavala:
A Framework for Democratizing AI. CoRR abs/2001.00818 (2020) - [i3]Rohan Mohapatra, Snehanshu Saha, Soma S. Dhavala:
AdaSwarm: A Novel PSO optimization Method for the Mathematical Equivalence of Error Gradients. CoRR abs/2006.09875 (2020) - [i2]Snehanshu Saha, Tejas Prashanth, Suraj Aralihalli, Sumedh Basarkod, T. S. B. Sudarshan, Soma S. Dhavala:
LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks. CoRR abs/2006.13307 (2020) - [i1]Chintan Donda, Sayan Dasgupta, Soma S. Dhavala, Keyur Faldu, Aditi Avasthi:
A framework for predicting, interpreting, and improving Learning Outcomes. CoRR abs/2010.02629 (2020)
2010 – 2019
- 2017
- [j1]Avishek Chakraborty, Derek Bingham, Soma S. Dhavala, Carolyn C. Kuranz, R. Paul Drake, Michael J. Grosskopf, Erica M. Rutter, Ben R. Torralva, James Paul Holloway, Ryan G. McClarren, Bani K. Mallick:
Emulation of Numerical Models With Over-Specified Basis Functions. Technometrics 59(2): 153-164 (2017)
Coauthor Index
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