Media Summary: MobileNetV1-3, Mnasnet, EfficientNets, Performers, RegNet Lecturer: Akhiad Bercovich. Mode Parallel, Gradient Accumulation, Data Parallel with PyTorch, Larger Batches Lecturer: Shai Bagon. Logistic regression, softmax classifier, cross entropy loss Lecturer: Niv Granot.
Dl4cv Wis Spring 2021 Tutorial - Detailed Analysis & Overview
MobileNetV1-3, Mnasnet, EfficientNets, Performers, RegNet Lecturer: Akhiad Bercovich. Mode Parallel, Gradient Accumulation, Data Parallel with PyTorch, Larger Batches Lecturer: Shai Bagon. Logistic regression, softmax classifier, cross entropy loss Lecturer: Niv Granot. Tensor operations, MLP implementation, Backpropagation, Optimizers Lecturer: Shir Amir. Introduction , Course logistics, Basic Supervised Learning setup, Linear regression, Normal equations, Gradient descent, Feature ... RNNs, LSTM, Tranformeres in Computer Vision Lecturer: Akhiad Bercovich.
SGD, Learning Rate Decay, Adam, Dropout, BatchNorm, Augmentations Lecturer: Shai Bagon. CNNs, Padding, Conv2D, Receptive Field, Transposed Convolution, Max Pooling Lecturer: Assaf Shocher. Vectorization, Broadcasting, Tensor Multiplication, Gather, Fold/Unfold, Dataloaders Lecturer: Ben Feinstein. Variational Auto Encoders (VAEs), Vector Quantize VAE (VQ-VAE), VQ-VAE2, DALL-E, Implicit Maximum Likelihood Estimation ... Deep Features, Image Embedding, Saliency via Occlusion, Class Activation Maps (CAM), Grad-CAM, Feature Inversion, Neural ... AlexNet, VGG, ResNet, EfficientNet Lecturer: Dror Moran.
Neurons, Backpropagation, SGD Lecturer: Assaf Shocher.
