Code for the paper 'On Learning Paradigms for the Travelling Salesman Problem' (NeurIPS 2019 Graph Representation Learning Workshop)
MIT License
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Code for "V1T: Large-scale mouse V1 response prediction using a Vision Transformer"
A library for ML benchmarking. It's powerful.
[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach
Experiments of Pytorch SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
PyTorch implementation of the CortexNet predictive model
A collection of state-of-the-art video or single-image super-resolution architectures, reimplemen...
Exploration of Self-Semi-Supervised learning for handling unlabeled data
🦄 State-of-the-Art Conversational AI with Transfer Learning
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Ima...
Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
Code for the paper 'Learning TSP Requires Rethinking Generalization' (CP 2021)
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Represent...
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Train high-quality text-to-image diffusion models in a data & compute efficient manner
Transformers are Graph Neural Networks!