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ORCIDAniruddha Adiga
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2020 – today
- 2023
[j3]Parantapa Bhattacharya
, Jiangzhuo Chen, Stefan Hoops, Dustin Machi, Bryan L. Lewis, Srinivasan Venkatramanan, Mandy L. Wilson, Brian Klahn, Aniruddha Adiga, Benjamin Hurt, Joseph Outten, Abhijin Adiga, Andrew S. Warren, Young Yun Baek, Przemyslaw J. Porebski, Achla Marathe, Dawen Xie, Samarth Swarup, Anil Vullikanti, Henning S. Mortveit, Stephen G. Eubank, Christopher L. Barrett, Madhav Vinayak Marathe:
Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support. Int. J. High Perform. Comput. Appl. 37(1): 4-27 (2023)- [c13]Aniruddha Adiga, Gursharn Kaur, Lijing Wang, Benjamin Hurt, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe:
Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts. AAAI 2023: 15647-15653 - [c12]Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Ambedkar Dukkipati, Tony Gracious, Shubham Gupta, Nihesh Rathod, Rajesh Sundaresan, Sarath Yasodharan, Kantha Rao Bhimala, Vidyadhar Mudkavi, Gopal Krishna Patra, Siva Athreya:
A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India. WSC 2023: 994-1005 - 2022
- [j2]Zakaria Mehrab, Aniruddha Adiga, Madhav V. Marathe, Srinivasan Venkatramanan, Samarth Swarup:
Evaluating the Utility of High-Resolution Proximity Metrics in Predicting the Spread of COVID-19. ACM Trans. Spatial Algorithms Syst. 8(4): 26:1-26:51 (2022) - [c11]Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav V. Marathe:
CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting. AAAI 2022: 12191-12199 - [c10]Aniruddha Adiga, Gursharn Kaur, Benjamin Hurt, Lijing Wang, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe:
Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources. IEEE Big Data 2022: 1594-1603 - 2021
- [c9]Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav V. Marathe, Rajesh Sundaresan, Milind Tambe:
Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway. AAMAS 2021: 1680-1682 - [c8]Aniruddha Adiga, Lijing Wang, Benjamin Hurt, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan Leroy Lewis, Madhav V. Marathe:
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting. KDD 2021: 2505-2513 - [c7]Benjamin Hurt, Aniruddha Adiga, Madhav V. Marathe, Christopher L. Barrett:
Informing University Covid-19 Decisions Using Simple Compartmental Models. WSC 2021: 1-12 - 2020
- [c6]Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan L. Lewis, Madhav V. Marathe:
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting. IEEE BigData 2020: 3846-3855 - [c5]Pavan Kulkarni, Jishnu Sadasivan, Aniruddha Adiga, Chandra Sekhar Seelamantula:
Epoch Estimation from a Speech Signal Using Gammatone Wavelets in a Scattering Network. ICASSP 2020: 7364-7368 - [i4]Aniruddha Adiga, Devdatt P. Dubhashi, Bryan L. Lewis, Madhav V. Marathe, Srinivasan Venkatramanan, Anil Vullikanti:
Models for COVID-19 Pandemic: A Comparative Analysis. CoRR abs/2009.10014 (2020) - [i3]Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan L. Lewis, Madhav V. Marathe:
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting. CoRR abs/2010.14491 (2020) - [i2]Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav V. Marathe, Rajesh Sundaresan, Milind Tambe:
Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway. CoRR abs/2012.12839 (2020)
2010 – 2019
- 2019
- [c4]Kenneth Tran, Ashkan Panahi, Aniruddha Adiga, Wesam A. Sakla, Hamid Krim:
Nonlinear Multi-scale Super-resolution Using Deep Learning. ICASSP 2019: 3182-3186 - 2018
- [c3]Sunil Rudresh, Aniruddha Adiga, Basty Ajay Shenoy, Chandra Sekhar Seelamantula:
Wavelet-Based Reconstruction for Unlimited Sampling. ICASSP 2018: 4584-4588 - 2017
- [i1]Aniruddha Adiga, Chandra Sekhar Seelamantula:
An Alternating Minimization Strategy for Sparse Blind Deconvolution - Convergence Analysis and Concentration Inequalities. CoRR abs/1708.07370 (2017) - 2014
- [j1]Arun Venkitaraman, Aniruddha Adiga, Chandra Sekhar Seelamantula:
Auditory-motivated Gammatone wavelet transform. Signal Process. 94: 608-619 (2014) - [c2]Aniruddha Adiga, Chandra Sekhar Seelamantula:
An alternating ℓp - ℓ2 projections algorithm (ALPA) for speech modeling using sparsity constraints. DSP 2014: 291-296 - [c1]Suraj Srinivas, Aniruddha Adiga, Chandra Sekhar Seelamantula:
Controlled blurring for improving image reconstruction quality in flutter-shutter acquisition. ICIP 2014: 5826-5830
Coauthor Index
aka: Madhav Vinayak Marathe
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