GPU Day 2026

Session

Session V

29 May 2026, 08:55

HUN-REN Centre

199. Fermionic Born Machines: Classical training of quantum generative models based on Fermion Sampling

Bence Bakó (Wigner RCP)

29/05/2026, 09:00

Quantum generative learning is a promising application of quantum computers, but faces several trainability challenges, including the difficulty in experimental gradient estimations. For certain structured quantum generative models, however, expectation values of local observables can be efficiently computed on a classical computer, enabling fully classical training without quantum gradient...

185. Generative modeling with Gaussian Boson Sampling: classically trainable Bosonic Born Machines

Zoltán Kolarovszki

29/05/2026, 09:20

Quantum generative modeling has emerged as a promising application of quantum computers, aiming to model complex probability distributions beyond the reach of classical methods. In practice, however, training such models often requires costly gradient estimation performed directly on the quantum hardware. Crucially, for certain structured quantum circuits, expectation values of local...

187. Search-Driven Quantum Circuit Decomposition

Gregory Morse (Eötvös Loránd University and Wigner RCP)

29/05/2026, 09:40

Lecture

Quantum circuit decomposition under restricted hardware connectivity is fundamentally a search problem: the compiler must choose useful qubit partitions, map them to a target topology, and synthesize high-quality local decompositions without exploding routing cost. This talk presents two complementary advances for connectivity-aware quantum compilation. First, we introduce an all-partitions...

188. Toward Autonomous Scientific Instrumentation: Real-Time AI Denoising and Control on FPGA–Groq Platforms

Peter Rakyta (Department of Physics of Complex Systems, Eötvös Loránd University)

29/05/2026, 10:00

Lecture

This project develops a hardware-accelerated, low-latency inference framework for real-time denoising and signal reconstruction in high-throughput, noise-limited measurement systems. While motivated by X-ray Free Electron Laser (XFEL) imaging, the proposed approach is designed to be broadly applicable to a wide range of data-intensive scientific and industrial domains, including plasma...