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Graph Neural Networks (GNNs) with Learnable Structural and Positional Representations
Saurav MaheshkarFeb 24Intermediate, Computer Vision, Molecule Generation, Research, GNN, Github, Plots
PoE-GAN: Generating Images from Multi-Modal Inputs
Soumik RakshitFeb 09Computer Vision, GenAI, Keras, Experiment, PoE-GAN, Panels, Plots, Tables, TMP, Exemplary
Tables Tutorial: Visualize Data for Image Classification
Stacey SvetlichnayaJul 18Intermediate, Computer Vision, Classification, Keras, Experiment, W&B Meta, Tables, iNaturalist, Chum here
DALL-E Mini Explained
Boris Dayma, Suraj Patil, Pedro Cuenca, Khalid Saifullah, Tanishq Abraham, Phúc Lê, Luke, Ritobrata GhoshAug 03Intermediate, Computer Vision, GenAI, OpenAI, Experiment, DALL-E, Panels, Plots, Sweeps, Tables, ImageNet, Large Models
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Interpretability in Deep Learning With Weights & Biases: CAM and Grad-CAM
Ayush ThakurApr 27Intermediate, Computer Vision, Object Detection, Keras, Experiment, CAM, Panels, Plots, Slider
Transfer Learning With the EfficientNet Family of Models
Sayak PaulApr 26Intermediate, Computer Vision, Classification, Transfer Learning, Keras, Experiment, EfficientNet, Plots, Cat v Dog
Exploring Bounding Boxes for Object Detection With Weights & Biases
Stacey SvetlichnayaApr 24Beginner, Computer Vision, Object Detection, W&B Meta, YOLO, Panels, Berkeley Deep Drive, Autonomous Vehicles
How Efficient Is EfficientNet?
Ajay ArasanipalaiApr 22Intermediate, Computer Vision, PyTorch, Research, EfficientNet, ResNet, Plots
Experimenting with EvoNorm Layers in TensorFlow 2
Sayak PaulApr 19Intermediate, Computer Vision, Classification, Keras, Research, EfficientNet, MobileNet v2, ResNet, Github, Plots, Sweeps, CIFAR10
Visualize, Track, and Compare fastai Models With Weights & Biases
Boris DaymaApr 17Beginner, Computer Vision, Semantic Segmentation, fastai, Tutorial, W&B Meta, Artifacts, Panels, Plots, Slider
Image Masks for Semantic Segmentation Using Weights & Biases
Stacey SvetlichnayaApr 16Intermediate, Computer Vision, Semantic Segmentation, W&B Meta, Slider, Berkeley Deep Drive
Towards Deep Generative Modeling With Weight & Biases
Ayush ThakurApr 14Intermediate, Computer Vision, GenAI, OCR, Keras, Experiment, Tutorial, GAN, Github, Panels, Plots, Sweeps, MNIST
Drought Watch Benchmark Progress
Stacey SvetlichnayaApr 11Intermediate, Computer Vision, Object Detection, Keras, Benchmark, Github, Plots, Sweeps
Digging Into KITTI With Weights & Biases With PyTorch-Lightning Kitti
Boris DaymaMar 29Intermediate, Computer Vision, Object Detection, Semantic Segmentation, PyTorch Lightning, Experiment, Github, Plots, Sweeps, KITTI, Autonomous Vehicles
Understanding State of the Art in Deep Learning: 3D Semantic Segmentation
Nicholas BardyFeb 22Intermediate, Computer Vision, 3D, Semantic Segmentation, Experiment, U-Net, Plots, ShapeNet
Curriculum Learning in Nature Using the iNaturalist 2017 Dataset
Stacey SvetlichnayaFeb 08Intermediate, Computer Vision, Object Detection, Experiment, CNN, Plots, iNaturalist
Classify the Natural World with Weights & Biases
Stacey SvetlichnayaFeb 08Advanced, Computer Vision, Object Detection, Keras, Experiment, CNN, Plots, ImageNet, iNaturalist, Exemplary
Hyperparameters of a Simple CNN Trained on Fashion MNIST
Stacey SvetlichnayaFeb 07Intermediate, Computer Vision, Object Detection, Experiment, CNN, Slider, Sweeps
Semantic Segmentation: The View from the Driver's Seat
Stacey SvetlichnayaFeb 06Advanced, Computer Vision, 3D, Object Detection, Semantic Segmentation, fastai, Experiment, CNN, ResNet, U-Net, Github, Panels, Plots, Slider, Sweeps, Berkeley Deep Drive, Autonomous Vehicles, Exemplary
Harness the Sky: Aerial Segmentation Benchmark with DroneDeploy
Stacey SvetlichnayaFeb 03Computer Vision
Meaning and Noise in Hyperparameter Search with Weights & Biases
Stacey SvetlichnayaJan 10Intermediate, Computer Vision, Object Detection, PyTorch, Experiment, RNN, Plots, Sweeps, MNIST
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