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…
Placing Degree Scales After LayerNorm
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…
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…