Bayesian and Neural Systems Group's repositories
nas-without-training
Code for Neural Architecture Search without Training (ICML 2021)
sequential-imagenet-dataloader
A plug-in replacement for DataLoader to load Imagenet disk-sequentially in PyTorch.
deep-kernel-transfer
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
pytorch-prunes
Code for https://arxiv.org/abs/1810.04622
pytorch-GENet
A Pytorch implementation of https://arxiv.org/abs/1810.12348.
pytorch-blockswap
Code for BlockSwap (ICLR 2020).
pytorch-moonshine
Cheap distillation for convolutional neural networks.
deficient-efficient
Successfully training approximations to full-rank matrices for efficiency in deep learning.
pytorch-experiments-template
A pytorch based classification experiments template
kubeproject
A set of tools built to simplify daily driving of cloud resources for individual VM access, Kubernetes batch jobs and miscellaneous useful functionality related to cloud-based ML research
self-supervised-relational-reasoning
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
codellmpersonalize
code for the llm personalize project
FewShotContinualLearning
The original code for the paper "Benchmarks for Continual Few-Shot Learning".
FewShotContinualLearningDataProvider
The original code for the data providers and the datasets of the paper "Defining Benchmarks for Continual Few-Shot Learning".
HowToTrainYourMAMLPytorch
The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.
learn2learn
A PyTorch Library for Meta-learning Research
Learning_to_Learn_via_Self-Critique
The original code for the paper "Learning to Learn via Self-Critique".
outline
The fastest knowledge base for growing teams. Beautiful, realtime collaborative, feature packed, and markdown compatible.
POEM-Bench
Welcome to GATE - Generalization After Transfer Evaluation - A framework built to evaluate a learning process on its ability to learn and generalize on previously unseen Tasks, Data domains and Modalities.
ptgood
Official repository for "Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning"
pytorch-experiments-template-docs
Documentation for the pytorch-experiments-template repo
Tutorial_BayesianCompressionForDL
A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).