Recently, the research team led by Professor Chen Zhong from the College of Electronic Science and Technology at Xiamen University has achieved significant strides in the realm of deep learning-driven reconstruction and uncertainty quantification for Laplace Nuclear Magnetic Resonance (NMR) spectra. The pertinent research outcomes have been published in the esteemed journal Science Advances, under the title "High-Confidence Reconstruction for Laplace Inversion in NMR Based on Uncertainty-Informed Deep Learning". This groundbreaking study marks the inaugural incorporation of uncertainty estimation into the Laplace NMR reconstruction process, enabling a dependable evaluation of quantitative results while simultaneously guaranteeing top-notch spectral analysis.