autoencoder-neural-network
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Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
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Oct 28, 2025 - Jupyter Notebook
Detecting malicious URLs using an autoencoder neural network
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Oct 9, 2022 - Python
Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.
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Nov 14, 2025 - TeX
Training Deep AutoEncoders for Collaborative Filtering
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Sep 9, 2019 - Jupyter Notebook
Using convolutional autoencoders to remove random noise from seismic data.
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Jun 10, 2021 - Jupyter Notebook
Code to train a custom time-domain autoencoder to dereverb audio
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Nov 30, 2023 - Python
Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models
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Apr 14, 2023 - Jupyter Notebook
Micro neural network with multi-dimensional layers, multi-shaped data, fully or locally meshing, conv2D, unconv2D, Qlearning, ... for test!
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Jan 8, 2021 - Python
All course material and codes of Generative Adversarial Networks Specialization offered by DeepLearning.ai
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Apr 29, 2023 - Jupyter Notebook
Image enhancement using GAN's and autoencoders
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Dec 8, 2022 - Java
Deep learning fraud detection system using MLP, Autoencoder, and VAE for imbalanced credit card data. Built with PyTorch, it includes SMOTE, RobustScaler preprocessing, FastAPI REST API for real-time predictions, and an interactive dashboard. Features EDA, ROC-AUC/PR-AUC evaluation, and unit tests.
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Aug 29, 2025 - Jupyter Notebook
Autoencoder for Feature Extraction
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Jun 1, 2022 - Jupyter Notebook
An automatic adjustment model is developed for brightness adjustment in images.
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May 23, 2022 - Jupyter Notebook
Anomaly detection (also known as outlier analysis) is a data mining step that detects data points, events, and/or observations that differ from the expected behavior of a dataset. A typical data might reveal significant situations, such as a technical fault, or prospective possibilities, such as a shift in consumer behavior.
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Dec 19, 2021 - Jupyter Notebook
Gemerator is an autoencoder based mixed gem image generator, also it has a website and web service written in Django and Flask and deployed using PythonAnywhere and Google Cloud, Respectively
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May 26, 2022 - JavaScript
Gaussian Latent Dirichlet Allocation
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Jan 26, 2022 - Jupyter Notebook
Bias field correction for T-1 weighted MRI images for tumor detection
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Sep 14, 2019 - Jupyter Notebook
Natural Disaster Analysis Website using Deep Learning & Poisson Distribution
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Apr 23, 2024 - Jupyter Notebook
This is my academic thesis work (individual). Submitted in partial fulfilment of the requirements for Degree of Bachelor of Science in Computer Science & Engineering
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Dec 13, 2024 - Jupyter Notebook
AI-driven web app | Image colorization using CNN autoencoders | implemented with Flask API
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Nov 17, 2023 - Jupyter Notebook
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