19 papers · ranked by Valyu relevance
Zou, Xiandong, Zhou Pan
Normalization is fundamental to deep learning, but existing approaches such as BatchNorm, LayerNorm, and RMSNorm are variance-centric by enforcing zero mean and unit variance, stabilizing training without controlling how representations capture task-relevant information. We propose IB-Inspired Normalization (IBNorm), a…
Khoat Than
In this work, we develop a theoretical framework that elucidates the role of normalization through the lens of capacity control. We prove that an unnormalized DNN can exhibit exponentially large Lipschitz constants with respect to either its parameters or inputs, implying excessive functional capacity and potential…
Ewa Roszkowska, Mario Martinelli
Normalization is a critical step in Multiple-Criteria Decision Analysis (MCDA) because it transforms heterogeneous criterion values into comparable information. This study examines normalization techniques through the lens of entropy, highlighting how criterion data structure shapes normalization behavior and ranking…
Karagodin, Nikita, Ge, Shu + 4 more
We study the effect of normalization schemes on token representations in deep transformers. Modeling their evolution as interacting particles on the sphere, we show that normalization acts as a form of speed regulation. This perspective enables a unified analysis of several schemes—including Post-LN, Pre-LN, Mix-LN…
Jatsada Singthongchai, Tanachapong Wangkhamhan, Zhiming Luo
This study presents a controlled benchmarking analysis of min-max scaling, Z-score normalization, and an adaptive preprocessing pipeline that combines percentile-based ROI cropping with histogram standardization. The evaluation was conducted across four public chest X-ray (CXR) datasets and three convolutional neural…
Qi Chu, Liu Peng, Lourdes Brea, Viriya Keo + 3 more
Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) is a powerful technology for studying genetic and epigenetic regulation. However, ChIP-seq data can be heavily affected by variations in chromatin amount and composition, ChIP enrichment, library preparation, and sequencing depth, affecting…
Yaqiang Cao, Guangzhe Ge, Keji Zhao
Sequencing-based epigenomic profiling methods are powerful but suffer from technical variability that complicates cross-sample comparisons and can obscure true biological signals. While existing normalization methods using spike-in controls or computational approaches have been proposed, they often rely on assumptions…
Mingzhi Chen, Taiming Lu, Jiachen Zhu, Mingjie Sun + 1 more
Figure 1 We introduce Dynamic erf (Derf), a point-wise function, that outperforms normalization layers and other point-wise functions. (a) We identify the feasible function shape for replacing the normalization layer and propose a large set of point-wise functions within this space. Evaluating all candidates, we…
Amen Al Khafaji, Carolina Gómez-Llorente, José Camacho
Normalization is a critical yet often poorly understood step in microbiome studies. Suboptimal approaches may lead to inaccurate conclusions in downstream analyses of microbial communities. Currently, there is no benchmarking framework to evaluate how normalisation affects both sample stratification and differential…
Deying Song, Douglas Ruff, Marlene Cohen, Chengcheng Huang
Neurons in higher-order visual areas integrate information through a canonical computation called normalization. The strength of normalization is highly heterogeneous across neurons, and this heterogeneity correlates with attention-mediated modulations in neural responses. However, the circuit mechanism underlying the…
Art Taychameekiatchai, Xiaowei Zhan, Guanghua Xiao, Peifeng Ruan
Spatial transcriptomics technologies enable measurement of gene expression while preserving spatial tissue organization, but they remain highly sensitive to technical variability such as library size differences, slide-level effects, and spatial artifacts. Most existing normalization approaches treat normalization as a…
Authors not listed
The discovery of chemically novel or structurally anomalous metal-organic frameworks (MOFs) is essential for expanding reticular design space and enhancing dataset reliability. We present CHEM-AD (Chemically Unusual Metal–organic Frameworks via Autoencoder-based Detection), a label-free, CPU-efficient pipeline that…
Behnaz Haji Molla Hoseyni, Sevda Imany, Ahmadreza Iranpour, Maryam Mehrabani + 4 more
Background Histology images are a cornerstone of pathology, which allow automated analysis for disease diagnosis. However, variations in staining and image acquisition processes significantly affect the performance of these algorithms. Histology image normalization is method to achieve uniformity in image color…
Alex Zelter, Michael Riffle, Gennifer E. Merrihew, Batool Mutawe + 8 more
Dogma suggests protein quantification is a pre-requisite to LC-MS/MS based proteomics studies. Such quantification allows a standardized ratio of sample to digestion enzyme and enables physical normalization of protein digest loaded onto the mass spectrometer for analysis. Most proteomics studies include these steps.…
David Gordillo-Alaniz, Eugenio Azpeitia
Understanding how signaling pathways reliably transmit information is fundamental to explaining cellular decision-making. Several studies have suggested that Dose–Response Alignment (DoRA) —the overlapping of dose–response curves between receptor occupancy and downstream responses— enhances information transmission by…
Authors not listed
Chemical bonding, despite being fundamental to chemistry, lacks a universally agreed-upon quantum mechanical definition that captures all its facets across diverse molecular systems. Traditional models—Lewis structures, Valence Bond theory, Molecular Orbital theory, and the Quantum Theory of Atoms in Molecules…
Modis, Theodore
Use is made of rigorous definitions for the terms normal, natural, and harmonic to reveal a number of unfamiliar aspects about them. The Gaussian distribution is not sufficient to determine who is normal, and fluctuations above or below a natural-growth curve may or may not be natural. A recipe for harmonically…
Authors not listed
Predicting which molecular systems require post-Hartree-Fock treatment remains a fundamental challenge in quantum chemistry. We introduce Fbond, a universal descriptor that quantifies electron correlation strength through the product of HOMO-LUMO gap and maximum single-orbital entanglement entropy. Validation across…
Authors not listed
Traditional electron-configuration notation (e.g. 1s^2 2s^2 2p^6) compresses multi-electron quantum information into integer occupancies that convey allowed maxima and most-probable arrangements but obscure the underlying probabilistic distribution and the spread of possible measurement outcomes. We present a…