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    Neural Networks

    2 482 курсов
    Backpropagation
    Capsule Networks
    ControlNet
    Convolutional Neural Networks (CNN)
    Feedforward Neural Networks
    Generative Adversarial Networks (GAN)
    Graph Neural Networks (GNN)
    Multilayer Perceptron
    Multilayer Perceptrons
    Neural Network Architecture
    Recurrent Neural Networks (RNN)
    Variational Autoencoder (VAE)
    Tensor-Train Decomposition and Its Applications in Machine Learning
    Institute for Pure & Applied Mathematics (IPAM)

    Tensor-Train Decomposition and Its Applications in Machine Learning

    On Sparse Linear Programming and Simple Neural Networks
    Institute for Pure & Applied Mathematics (IPAM)

    On Sparse Linear Programming and Simple Neural Networks

    A Mathematical Perspective on Machine Learning
    International Mathematical Union

    A Mathematical Perspective on Machine Learning

    Composing Graphical Models with Neural Networks for Structured Representations and Fast Inference
    Simons Institute

    Composing Graphical Models with Neural Networks for Structured Representations and Fast Inference

    Geometry, Optimization and Generalization in Multilayer Networks
    Simons Institute

    Geometry, Optimization and Generalization in Multilayer Networks

    Tutorial on Deep Learning IV
    Simons Institute

    Tutorial on Deep Learning IV

    Tutorial on Deep Learning I
    Simons Institute

    Tutorial on Deep Learning I

    Statistical Learning Theory and Neural Networks II
    Simons Institute

    Statistical Learning Theory and Neural Networks II

    Statistical Learning Theory and Neural Networks
    Simons Institute

    Statistical Learning Theory and Neural Networks

    Adversarial Examples in Deep Learning
    Simons Institute

    Adversarial Examples in Deep Learning

    Orthogonal Statistical Learning
    Simons Institute

    Orthogonal Statistical Learning

    Towards Verification of General Neural Networks: A Dual Approach
    Simons Institute

    Towards Verification of General Neural Networks: A Dual Approach

    In Search of New Algorithms Part I - Neural Networks
    Simons Institute

    In Search of New Algorithms Part I - Neural Networks

    The Interpolation Phase Transition in Neural Networks - Memorization and Generalization Lazy Training
    Simons Institute for the Theory of Computing

    The Interpolation Phase Transition in Neural Networks - Memorization and Generalization Lazy Training

    Learning One-Hidden-Layer Neural Networks with Landscape Design
    Simons Institute for the Theory of Computing

    Learning One-Hidden-Layer Neural Networks with Landscape Design

    Deep Neural Networks for YouTube Recommendations
    Aladdin Persson

    Deep Neural Networks for YouTube Recommendations

    Information Flow and Deep Representation Learning
    Open Data Science

    Information Flow and Deep Representation Learning

    Automated Hyperparameter Tuning for Deep Neural Networks
    Abhishek Thakur

    Automated Hyperparameter Tuning for Deep Neural Networks

    What Are CycleGANs? - A Novel Deep Learning Tool in Pathology
    Abhishek Thakur

    What Are CycleGANs? - A Novel Deep Learning Tool in Pathology

    Captcha Recognition Using PyTorch - Convolutional-RNN + CTC Loss
    Abhishek Thakur

    Captcha Recognition Using PyTorch - Convolutional-RNN + CTC Loss

    Image Restoration Using Deep Learning - Dehazing
    Abhishek Thakur

    Image Restoration Using Deep Learning - Dehazing