22 papers · ranked by Valyu relevance
Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang + 2 more
'Zhenguo Li'] In recent years, a variety of normalization methods have been proposed to help train neural networks, such as batch normalization (BN), layer normalization (LN), weight normalization (WN), group normalization (GN), etc. However, mathematical tools to analyze all these normalization methods are lacking. In…
Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz + 1 more
'Richard S. Zemel'] Normalization techniques have only recently begun to be exploited in supervised learning tasks. Batch normalization exploits mini-batch statistics to normalize the activations. This was shown to speed up training and result in better models. However its success has been very limited when dealing…
Xu Pan, Luis Gonzalo Sánchez Giraldo, Elif Kartal, Odelia Schwartz
We studied a local normalization paradigm, namely weighted normalization, that better reflects the current understanding of the brain. Specifically, the normalization weight is trainable, and has a more realistic surround pool selection. Weighted normalization outperformed other normalizations in image classification…
Zaina A. Zayyad, John H. R. Maunsell, Jason N. MacLean
When multiple stimuli appear together in the receptive field of a visual cortical neuron, the response is typically close to the average of that neuron’s response to each individual stimulus. The departure from a linear sum of each individual response is referred to as normalization. In mammals, normalization has been…
Flaviano Morone, Shivang Rawat, David J. Heeger, Stefano Martiniani
Stability is a fundamental requirement for both biological and engineered neural circuits, yet it is surprisingly difficult to guarantee in the presence of recurrent interactions. Standard linear dynamical models of recurrent networks are sensitive to the precise values of the synaptic weights, since stability requires…
Max Robinson
A numerical data matrix may be seen simply as a means of organizing observations of a system into rows in one manner (e.g., by measured "object"), and into columns by another (e.g., by measured "variable") so that the observations can be analyzed with mathematical tools. As a mathematical object, however, a matrix…
Rui Xie, Mengrui Zhang, Prahatha Venkatraman, Xinlian Zhang + 9 more
'Gaonan Zhang' 'Robert Carmer' 'Skylar A. Kantola' 'Chi Pui Pang' 'Ping Ma' 'Mingzhi Zhang' 'Wenxuan Zhong' 'Yuk Fai Leung' 'Stephan C.F. Neuhauss'] Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often…
Anath Rau Krishnan
The use of a multi-criteria decision-making (MCDM) technique mostly begins with normalizing the incommensurable data values in the decision matrix. Numerous normalization methods are available in the literature and applying different normalization methods to an MCDM technique is proven to deliver varying results. As…
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…
Massimiliano Esposito, Nader Ganaba
As the deep neural networks are being applied to complex tasks, the size of the networks and architecture increases and their topology becomes more complicated too. At the same time, training becomes slow and at some instances inefficient. This motivated the introduction of various normalization techniques such as…
Daniel Eftekhari, Vardan Papyan
The normal distribution plays a central role in information theory – it is at the same time the best-case signal and worst-case noise distribution, has the greatest representational capacity of any distribution, and offers an equivalence between uncorrelatedness and independence for joint distributions. Accounting for…
Róbert Rajkó
This short communication paper is briefly dealing with greater or lesser misused normalization in self-modeling/multivariate curve resolution (S/MCR) practice. The importance of the correct use of the ODE (ordinary differential equation) solvers and apt kinetic illustrations are elucidated. The new terms, external and…
Ruben Coen-Cagli, Selina S. Solomon
Cortical responses to repeated presentations of a stimulus are variable. This variability is sensitive to experimental manipulations that are also known to engage divisive normalization: a widespread description of neural activity as the ratio of a numerator (the excitatory stimulus drive) and denominator (the…
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…
Shadrack Barnabas, Timo Böhme, Stephen Boyer, Matthias Irmer + 4 more
The extraction of chemical information from documents is a demanding task in cheminformatics due to the variety of text and image-based representations of chemistry. The present work describes the extraction of chemical compounds with unique chemical structures from the open access CORE (COnnecting REpositories) and…
Shadrack Barnabas, Timo Böhme, Stephen Boyer, Matthias Irmer + 5 more
The extraction of chemical information from documents is a demanding task in cheminformatics due to the variety of text and image-based representations of chemistry. The present work describes the extraction of chemical compounds with unique chemical structures from the open access CORE (COnnecting REpositories) and…
Authors not listed
Meteorological normalization is a key concept in studying anthropogenic effects on air pollutant concentrations and its temporal trends. While apparently successful in revealing anthropogenic effects and often used, there are downsides to the methods and limitations which should be taken into account when using it.…
Authors not listed
STO-mG type basis functions for 1s to 4f Hydrogen-like orbitals by “energy fit” are reported as simple functions of running parameter atomic number Z and quantum numbers to utilize the basis set from these functions in molecular electronic structure and energy calculations. We mimic the accurate solution of Slater-type…
Saige Rutherford, Pieter Barkema, Ivy F. Tso, Chandra Sripada + 3 more
In this work, we expand the normative model repository introduced in Rutherford et al. (2022a) to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online…
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…
Philip D. Gingerich
The zero-force evolutionary law (ZFEL) of McShea et al. states that independently evolving entities, with no forces or constraints acting on them, will tend to accumulate differences and therefore diverge from each other. McShea et al. quantified the law by assuming normality on an additive arithmetic scale and…
Abhranil Das, Wilson S. Geisler
Univariate and multivariate normal probability distributions are widely used when modeling decisions under uncertainty. Computing the performance of such models requires integrating these distributions over specific domains, which can vary widely across models. Besides some special cases where these integrals are easy…