AIMC Topic: Normal Distribution

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Towards a configurable and non-hierarchical search space for NAS.

Neural networks : the official journal of the International Neural Network Society
Neural Architecture Search (NAS) outperforms handcrafted Neural Network (NN) design. However, current NAS methods generally use hard-coded search spaces, and predefined hierarchical architectures. As a consequence, adapting them to a new problem can ...

Conformations of KRAS4B Affected by Its Partner Binding and G12C Mutation: Insights from GaMD Trajectory-Image Transformation-Based Deep Learning.

Journal of chemical information and modeling
Binding of partners and mutations highly affects the conformational dynamics of KRAS4B, which is of significance for deeply understanding its function. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) and prin...

Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

Molecules (Basel, Switzerland)
CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (...

Learning active subspaces and discovering important features with Gaussian radial basis functions neural networks.

Neural networks : the official journal of the International Neural Network Society
Providing a model that achieves a strong predictive performance and is simultaneously interpretable by humans is one of the most difficult challenges in machine learning research due to the conflicting nature of these two objectives. To address this ...

Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.

Medical & biological engineering & computing
Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level poses a challenge as each pixel does not reflect any semantic entities. Furthermo...

Frequency compensated diffusion model for real-scene dehazing.

Neural networks : the official journal of the International Neural Network Society
Due to distribution shift, deep learning based methods for image dehazing suffer from performance degradation when applied to real-world hazy images. In this paper, this study considers a dehazing framework based on conditional diffusion models for i...

An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.

Journal of chemical information and modeling
Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization ap...

Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized glass slide, called Whole Slide Image (WSI), for further examination. These procedures frequently int...

Pumping machine fault diagnosis based on fused RDC-RBF.

PloS one
At present, the fault diagnosis of pumping units in major oil fields in China is time-consuming and inefficient, and there is no universal problem for high requirements of hardware resources. In this study, a fault fusion diagnosis method of pumping ...

Statistically unbiased prediction enables accurate denoising of voltage imaging data.

Nature methods
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pix...