29 projects for "python windows" with 2 filters applied:

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  • 1
    distribution-is-all-you-need

    distribution-is-all-you-need

    The basic distribution probability Tutorial for Deep Learning Research

    distribution-is-all-you-need is a Python-based probability tutorial aimed at deep learning researchers and students. It explains common discrete and continuous distributions through short scripts, formulas, descriptions, and plotted graphs. Covered topics include uniform, Bernoulli, binomial, categorical, multinomial, beta, Dirichlet, gamma, exponential, Gaussian, normal, chi-squared, and Student's t distributions. The material highlights relationships such as conjugate priors and...
    Downloads: 1 This Week
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  • 2
    LearningToCompare_FSL

    LearningToCompare_FSL

    Learning to Compare: Relation Network for Few-Shot Learning

    LearningToCompare_FSL is a PyTorch implementation of the “Learning to Compare: Relation Network for Few-Shot Learning” paper, focusing on the few-shot learning experiments described in that work. The core idea implemented here is the relation network, which learns to compare pairs of feature embeddings and output relation scores that indicate whether two images belong to the same class, enabling classification from only a handful of labeled examples. The repository provides training and...
    Downloads: 0 This Week
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  • 3
    Deep Reinforcement Learning TensorFlow

    Deep Reinforcement Learning TensorFlow

    TensorFlow implementation of Deep Reinforcement Learning papers

    Deep Reinforcement Learning TensorFlow is a comprehensive TensorFlow codebase that implements several foundational deep reinforcement learning algorithms for educational and experimental use. The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural...
    Downloads: 0 This Week
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  • 4
    PassGAN

    PassGAN

    A Deep Learning Approach for Password Guessing

    PassGAN is a research implementation of a generative adversarial network trained to model human password patterns. It reproduces ideas from the paper “PassGAN: A Deep Learning Approach for Password Guessing” using a modified Wasserstein GAN implementation. The repository includes scripts for training models and generating candidate password samples from learned distributions. A pretrained model based on the RockYou dataset is provided for reproducing experiments. TensorFlow and CUDA were...
    Downloads: 8 This Week
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