Ramakrishna Tipireddy

19 papers A* 1C 1Misc 1Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	C	`conf`	Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning. ICMLA Katarzyna Borowiec, Dan Lu, Vikas Chandan, Samrat Chatterjee, Pradeep Ramuhalli, Ramakrishna Tipireddy, Mahantesh Halappanavar, Frank Liu
2023	J	`jnl`	Conditional Korhunen-Loéve regression model with Basis Adaptation for high-dimensional problems: uncertainty quantification and inverse modeling. CoRR Yu-Hong Yeung, Ramakrishna Tipireddy, David A. Barajas-Solano, Alexandre M. Tartakovsky
2023	A*	`conf`	Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains. ICML Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy, Mahantesh M. Halappanavar
2022	J	`jnl`	Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains. CoRR Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy, Mahantesh Halappanavar
2021	J	`jnl`	Lorenz System State Stability Identification using Neural Networks. CoRR Megha Subramanian, Ramakrishna Tipireddy, Samrat Chatterjee
2021	J	`jnl`	Time-dependent stochastic basis adaptation for uncertainty quantification. CoRR Ramakrishna Tipireddy, Panos Stinis, Alexandre M. Tartakovsky
2020	J	`jnl`	An efficient epistemic uncertainty quantification algorithm for a class of stochastic models: A post-processing and domain decomposition framework. CoRR Mahadevan Ganesh, Stuart C. Hawkins, Alexandre M. Tartakovsky, Ramakrishna Tipireddy
2020	J	`jnl`	Bayesian phase estimation with adaptive grid refinement. CoRR Ramakrishna Tipireddy, Nathan Wiebe
2020	J	`jnl`	Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models. J. Comput. Phys. Ramakrishna Tipireddy, David A. Barajas-Solano, Alexandre M. Tartakovsky
2020	J	`jnl`	FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation. CoRR Arnab Das, Sriram Krishnamoorthy, Ian Briggs, Ganesh Gopalakrishnan, Ramakrishna Tipireddy
2020	J	`jnl`	FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation. ACM Trans. Archit. Code Optim. Arnab Das, Sriram Krishnamoorthy, Ian Briggs, Ganesh Gopalakrishnan, Ramakrishna Tipireddy
2020	J	`jnl`	Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids. CoRR Tong Ma, David Alonso Barajas-Solano, Ramakrishna Tipireddy, Alexandre M. Tartakovsky
2019	J	`jnl`	A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations. CoRR Ramakrishna Tipireddy, Paris Perdikaris, Panos Stinis, Alexandre M. Tartakovsky
2019	J	`jnl`	Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression. CoRR Tong Ma, Renke Huang, David A. Barajas-Solano, Ramakrishna Tipireddy, Alexandre M. Tartakovsky
2019	—	`conf`	Physics-informed Machine Learning Method for Forecasting and Uncertainty Quantification of Partially Observed and Unobserved States in Power Grids. HICSS Alexandre M. Tartakovsky, Ramakrishna Tipireddy
2018	Misc	`conf`	Quantification, Trade-off Analysis, and Optimal Checkpoint Placement for Reliability and Availability. HiPC Omer Subasi, Ramakrishna Tipireddy, Sriram Krishnamoorthy
2018	J	`jnl`	Stochastic Basis Adaptation and Spatial Domain Decomposition for Partial Differential Equations with Random Coefficients. SIAM/ASA J. Uncertain. Quantification Ramakrishna Tipireddy, Panos Stinis, Alexandre M. Tartakovsky
2017	J	`jnl`	Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients. J. Comput. Phys. Ramakrishna Tipireddy, Panos Stinis, Alexandre M. Tartakovsky
2014	J	`jnl`	Basis adaptation in homogeneous chaos spaces. J. Comput. Phys. Ramakrishna Tipireddy, Roger G. Ghanem