2 papers
eess.AS2025
Bridging the Gap between Continuous and Informative Discrete Representations by Random Product Quantization
Xueqing Li, Hao Ma, Zehan Li +8
Self-supervised learning (SSL) has become a core technique in speech processing, but the high dimensionality of its representations makes discretization essential for improving eff…
quant-ph2025
QGHNN: A quantum graph Hamiltonian neural network
Wenxuan Wang
Representing and learning from graphs is essential for developing effective machine learning models tailored to non-Euclidean data. While Graph Neural Networks (GNNs) strive to add…