4 papers
Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing
Yash Vardhan Tomar, Dheeraj Peddireddy
Quantum circuit routing is a key step in compiling programs for noisy intermediate-scale quantum processors, particularly superconducting devices whose sparse fixed coupling makes…
SymQNet: Amortized Acquisition for Low-Latency Adaptive Hamiltonian Learning
Yash Vardhan Tomar, Dheeraj Peddireddy
Adaptive Hamiltonian learning is central to calibrating and characterizing quantum devices. In an adaptive controller, choosing the next experiment is itself a computation. Bayesia…
What Must a Fairness Audit Report When Demographic Data Is Incomplete?
Yash Vardhan Tomar
Fairness audits are a key component of responsible machine-learning deployment. Yet what such an audit must disclose, when the protected labels it depends on are incomplete, remain…
Placing Degree Scales After LayerNorm
Yash Tomar, Yash Vardhan Tomar, Aryav Das
Graph neural networks (GNNs) are widely used to learn node-selection policies on graphs, and most stack graph attention (GAT) blocks with LayerNorm. On degree-sensitive tasks, Laye…