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Vim-fork focused on extensibility and usability
Official PyTorch implementation for Frequency Domain-based Dataset Distillation [NeurIPS 2023]
Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
Uncertainty-aware representation learning (URL) benchmark
Legible, Scalable, Reproducible Foundation Models with Named Tensors and Jax
Neighborhood Attention Transformer, arxiv 2022 / CVPR 2023. Dilated Neighborhood Attention Transformer, arxiv 2022
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
Toolbox of models, callbacks, and datasets for AI/ML researchers.
A Python package of computer vision models for the Equinox ecosystem.
JAX - A curated list of resources https://github.com/google/jax
A selection of neural network models ported from torchvision for JAX & Flax.
Automatic generation of documentation for mkdocs
👋 Xplique is a Neural Networks Explainability Toolbox
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Differentiable optical models as parameterised neural networks in Jax using Zodiax
Fine-grained, dynamic control of neural network topology in JAX.
Hierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc.
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
Uncertainty in Deep Learning Papers
Preparing for machine learning interviews
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
A curated list of awesome Deep Learning tutorials, projects and communities.
A curated list of deep learning resources for computer vision