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#machine learning Preprint Aug 2026

RamanPFN: learning from Raman spectral structure with a tabular foundation model

RamanPFN is presented, a spectral representation framework that encodes dependencies before TabPFN inference and establishes explicit spectral representation as an effective interface between high-dimensional Raman measurements and reusable tabular inference.

Xing-Yu Pan, Huanfei Wang, Jin-Jiang Guo et al. · 1 citation
#machine learning Preprint Sep 2026

Response-state Learning for Transferable Vibrational Spectroscopic Characterization with Electron Prior

Vibrational spectral prediction can become inaccurate when localized stereoelectronic environments perturb intermediate response states and high-risk response units dominate characteristic spectral fingerprints, making prediction across external chemical space difficult. SO(3) Equivariant Neural Kalman Networks (SENK)...

Ze-Tong Li, Zhuo-Song Xie, Heng-Yu Fan et al. · 0 citations
Open access Aug 2026

Spectral Contrast Features: A Bin-Difference Approach to Interpretable, Parsimonious, and Cross-Instrument NIR Calibration

Near-infrared (NIR) spectroscopy with full-spectrum chemometric modeling is widely used in food, agricultural, and pharmaceutical analysis, but calibrations resting on hundreds to thousands of spectral variables are difficult to audit and require full-spectrum instrumentation to deploy. The Spectral Contrast Feature (S...

Prabesh Joshi · 0 citations
Preprint Aug 2026

Simulation-to-real transfer learning for infrared spectroscopic chemical sensing and analysis from molecules to complex samples

UltraIR is introduced, a foundation model for IR spectroscopy with more than 100 million parameters that enables simulation-to-real transfer learning for chemical sensing and analysis from molecules to complex samples and outperforms conventional machine-learning and task-specific deep-learning baselines.

Yu-Sen Tan, Yixuan Chen, Zheng Fang et al. · 0 citations
Preprint Sep 2026

Automated feature-region selection for soft-sensor development from spectral-like measurements

Sustainable production increasingly relies on process analytical chemistry and process analytical technology to support monitoring, control, and automation. Techniques used in these contexts, including Raman spectroscopy, infrared spectroscopy, and electrochemical voltammetry, generate high-dimensional signals ordered...

Sebastián Espinel-Ríos, Wen-Chao Duan · 0 citations
Aug 2026

Principal Component Analysis Based Deconvolution of NMR Chemical Shifts for Objective Biomolecular Interaction Mapping

PALI (principal component analysis for ligand interactions), an objective and PCA-based framework designed to standardize multivariate NMR analysis, is introduced, bridging the gap between advanced multivariate statistics and routine structural biology workflows.

Min June Yang, Joonhyeok Choi, Hyeonjun Lee et al. · 0 citations

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