From 19c21707ef34eab3ca2f30719dfbf758466fc310 Mon Sep 17 00:00:00 2001 From: Christophe Pere Date: Fri, 28 Feb 2025 16:20:52 -0500 Subject: [PATCH] Update 2025.md --- 2025/2025.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/2025/2025.md b/2025/2025.md index b6191f6..f44095d 100644 --- a/2025/2025.md +++ b/2025/2025.md @@ -9,13 +9,17 @@ - [Asaoka & Kudo, 2025, Quantum autoencoders for image classification](https://arxiv.org/pdf/2502.15254) - [Babu et al., 2025, Gate teleportation-assisted routing for quantum algorithms](https://arxiv.org/pdf/2502.04138) - [Bal et al., 2025, 1 Particle - 1 Qubit: Particle Physics Data Encoding for Quantum Machine Learning](https://arxiv.org/pdf/2502.17301) +- [Berti et al., 2025, Quantum Machine Learning in Precision Medicine and Drug Discovery -- A Game Changer for Tailored Treatments?](https://arxiv.org/pdf/2502.18639) - [Chen et al., 2025, Learning to Measure Quantum Neural Networks](https://arxiv.org/pdf/2501.05663) - [Chen et al., 2025, Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate Predictions](https://arxiv.org/pdf/2501.15828) - [Coelho & Kruse & Rosskopf, 2025, Quantum-Efficient Kernel Target Alignment](https://arxiv.org/pdf/2502.08225) - [Coroi & Oh, 2025, Exponential advantage in continuous-variable quantum state learning](https://arxiv.org/pdf/2501.17633) +- [Dell'Anna et al., 2025, Quantum Natural Gradient optimizer on noisy platforms: QAOA as a case study](https://arxiv.org/pdf/2502.20288) - [Fleury & Lacomme, 2025, Quantum circuit for exponentiation of Hamiltonians: an algorithmic description based on tensor products](https://arxiv.org/pdf/2501.17780) +- [Galvão et al., 2025, Simulating Work Extraction in a Dinuclear Quantum Battery Using a Variational Quantum Algorithm](https://arxiv.org/pdf/2502.19331) - [Galvis-Florez & Farooq & Särkkä, 2025, Provable Quantum Algorithm Advantage for Gaussian Process Quadrature](https://arxiv.org/pdf/2502.14467) - [Gerlach, et al. 2025, Hybrid Quantum-Classical Multi-Agent Pathfinding](https://arxiv.org/pdf/2501.14568) +- [Hoch et al., 2025, Quantum machine learning with Adaptive Boson Sampling via post-selection](https://arxiv.org/pdf/2502.20305) - [Joch & Uhrig & Fauseweh, 2025, Entanglement-informed Construction of Variational Quantum Circuits](https://arxiv.org/pdf/2501.17533) - [Kairon & Jäger & Krems, 2025, Equivalence between exponential concentration in quantum machine learning kernels and barren plateaus in variational algorithms](https://arxiv.org/pdf/2501.07433) - [Kasture et al., 2025, Multiparticle quantum walks for distinguishing hard graphs](https://arxiv.org/pdf/2501.03683) @@ -51,11 +55,13 @@ - [Tomar & Tripathi & Kumar, 2025, Comprehensive Survey of QML: From Data Analysis to Algorithmic Advancements](https://arxiv.org/pdf/2501.09528) - [Vasques & Paik & Cif, 2025, Application of quantum machine learning using quantum kernel algorithms on multiclass neuron M type classification](https://arxiv.org/pdf/2502.06281) - [Villar-Rodriguez et al., 2025, On the Transfer of Knowledge in Quantum Algorithms](https://arxiv.org/pdf/2501.14120) +- [Vyas & Santhanam, 2025, Extreme Events of Quantum Walks on Graphs](https://arxiv.org/pdf/2502.19355) - [Wang et al., 2025, GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching](https://arxiv.org/abs/2501.00135v1) - [Wang, 2025, QGHNN: A quantum graph Hamiltonian neural network](https://arxiv.org/pdf/2501.07986) - [Wang, 2025, Noise-resistant adaptive Hamiltonian learning](https://arxiv.org/pdf/2501.08017) - [Wang et al., 2025, Towards efficient quantum algorithms for diffusion probability models](https://arxiv.org/pdf/2502.14252) - [Xu & Aggarwal, 2025, Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach](https://arxiv.org/pdf/2501.16243) +- [Zhang et al., 2025, Hamiltonian Learning at Heisenberg Limit for Hybrid Quantum Systems](https://arxiv.org/pdf/2502.20373) - [Zia et al., 2025, Quantum extreme learning machines for photonic entanglement witnessing](https://arxiv.org/pdf/2502.18361) - [Zimboràs et al., 2025, Myths around quantum computation before full fault tolerance: What no-go theorems rule out and what they don’t](https://arxiv.org/pdf/2501.05694)