Abhijith Jayakumar

15 papers A* 2Misc 1Journal 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Computationally sufficient statistics for Ising models.
CoRR
Abhijith Jayakumar, Shreya Shukla, Marc Vuffray, Andrey Y. Lokhov, Sidhant Misra
2026 J jnl
Discrete Diffusion with Sample-Efficient Estimators for Conditionals.
CoRR
Karthik Elamvazhuthi, Abhijith Jayakumar, Andrey Y. Lokhov
2025 J jnl
Efficient Learning of Lattice Gauge Theories with Fermions.
CoRR
Shreya Shukla, Yukari Yamauchi, Andrey Y. Lokhov, Scott Lawrence, Abhijith Jayakumar
2025 A* conf
Optimization Proxies using Limited Labeled Data and Training Time - A Semi-Supervised Bayesian Neural Network Approach.
ICML
Parikshit Pareek, Abhijith Jayakumar, Kaarthik Sundar, Sidhant Misra, Deepjyoti Deka
2024 J jnl
Demystifying Quantum Power Flow: Unveiling the Limits of Practical Quantum Advantage.
CoRR
Parikshit Pareek, Abhijith Jayakumar, Carleton Coffrin, Sidhant Misra
2024 J jnl
Discrete distributions are learnable from metastable samples.
CoRR
Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
2024 J jnl
Universal framework for simultaneous tomography of quantum states and SPAM noise.
Quantum
Abhijith Jayakumar, Stefano Chessa, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
2023 Misc conf
General Algorithms for SPAM Noise Characterization.
QCE
Abhijith Jayakumar, Stefano Chessa, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
2023 J jnl
Learning Energy-Based Representations of Quantum Many-Body States.
CoRR
Abhijith Jayakumar, Marc Vuffray, Andrey Y. Lokhov
2022 J jnl
Quantum Algorithm Implementations for Beginners.
ACM Trans. Quantum Comput.
Abhijith Jayakumar, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balu Nadiga, Daniel O'Malley, Diane Oyen, Scott Pakin, Lakshman Prasad, Randy Roberts, Phillip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, James G. Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu, Stephan J. Eidenbenz, Andreas Bärtschi, Patrick J. Coles, Marc Vuffray, Andrey Y. Lokhov
2022 J jnl
Reliable quantum kernel classification using fewer circuit evaluations.
CoRR
Abhay Shastry, Abhijith Jayakumar, Apoorva D. Patel, Chiranjib Bhattacharyya
2020 A* conf
Learning of Discrete Graphical Models with Neural Networks.
NeurIPS
Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
2020 J jnl
Learning of Discrete Graphical Models with Neural Networks.
CoRR
Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
2019 J jnl
Improving quantum spatial search in two dimensions.
Quantum Inf. Comput.
Abhijith Jayakumar, Apoorva D. Patel
2018 J jnl
Spatial search using flip-flop quantum walk.
Quantum Inf. Comput.
Abhijith Jayakumar, Apoorva D. Patel