Kavitha Yogaraj

IBM Research - India — India

Computer Science · Physical Sciences

4h-index25citations15works1.82yr avg
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Research Topics

Quantum Computing Algorithms and Architecture(7), Quantum Information and Cryptography(6), Quantum Mechanics and Applications(2), Electric Vehicles and Infrastructure(2), Data Visualization and Analytics(2)

Publications15 total

Mitigating exponential concentration in covariant quantum kernels for subspace and real-world data
npj Quantum Information·2025Open Access
Post-variational classical quantum transfer learning for binary classification
Scientific Reports·2025· 2 citedOpen Access
Conditions for a quadratic quantum speedup in nonlinear transforms with applications to energy contract pricing
Quantum Science and Technology·2024· 4 citedOpen Access
Mitigating exponential concentration in covariant quantum kernels for subspace and real-world data
arXiv (Cornell University)·2024Open Access
A Machine Learning Approach to Boost the Vehicle-2-Grid Scheduling
2024· 1 cited
A Machine Learning Approach to Boost the Vehicle-2-Grid Scheduling
arXiv (Cornell University)·2024Open Access
A Survey of Classical and Quantum Sequence Models
2024· 2 cited
Energy Risk Analysis With Dynamic Amplitude Estimation and Piecewise Approximate Quantum Compiling
IEEE Transactions on Quantum Engineering·2024· 5 citedOpen Access
A Survey of Classical And Quantum Sequence Models
arXiv (Cornell University)·2023· 1 citedOpen Access
Energy risk analysis with Dynamic Amplitude Estimation and Piecewise Approximate Quantum Compiling
arXiv (Cornell University)·2023Open Access
Conditions for a quadratic quantum speedup in nonlinear transforms with applications to energy contract pricing
arXiv (Cornell University)·2023· 5 citedOpen Access
Gamma-hadron Separation in Imaging Atmospheric Cherenkov Telescopes using Quantum Classifiers
arXiv (Cornell University)·2022Open Access
Study of Feature Importance for Quantum Machine Learning Models
arXiv (Cornell University)·2022· 5 citedOpen Access
Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football\n Player Trades
arXiv (Cornell University)·2021Open Access
Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades
arXiv (Cornell University)·2021Open Access

Frequent Co-authors

Gabriele Agliardi(8), Kumar Ghosh(8), G. Cortiana(7), Corey O’Meara(5), Piergiacomo Sabino(4), Omar Shehab(4), Anton Dekusar(4), Naeimeh Mohseni(4), Víctor Valls(4), Sergiy Zhuk(4), Marina Fernández-Campoamor(3), Juan Bernabé-Moreno(3), Aaron K. Baughman(3), Raja Hebbar(3), Sudeep Ghosh(3), Rukhsan Ul Haq(3), Yoshika Chhabra(3), Brian Quanz(3), Corey O’Meara(3), Francesco Tacchino(2)