rtanno21609's Stars
Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
microsoft/SPTAG
A distributed approximate nearest neighborhood search (ANN) library which provides a high quality vector index build, search and distributed online serving toolkits for large scale vector search scenario.
SeldonIO/seldon-core
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
subeeshvasu/Awesome-Learning-with-Label-Noise
A curated list of resources for Learning with Noisy Labels
voxelmorph/voxelmorph
Unsupervised Learning for Image Registration
facebookresearch/fvcore
Collection of common code that's shared among different research projects in FAIR computer vision team.
fairlearn/fairlearn
A Python package to assess and improve fairness of machine learning models.
uncertainty-toolbox/uncertainty-toolbox
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
AgaMiko/data-augmentation-review
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
GMvandeVen/continual-learning
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
google/uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
facebookresearch/DomainBed
DomainBed is a suite to test domain generalization algorithms
MedMNIST/MedMNIST
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
jonbarron/robust_loss_pytorch
A pytorch port of google-research/google-research/robust_loss/
AlaaLab/deep-learning-uncertainty
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
EmuKit/emukit
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
microsoft/InnerEye-DeepLearning
Medical Imaging Deep Learning library to train and deploy 3D segmentation models on Azure Machine Learning
facebookresearch/InvariantRiskMinimization
PyTorch code to run synthetic experiments.
kuc2477/pytorch-ewc
Unofficial PyTorch implementation of DeepMind's PNAS 2017 paper "Overcoming Catastrophic Forgetting"
rtanno21609/AdaptiveNeuralTrees
Adaptive Neural Trees
equialgo/fairness-in-ml
This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
microsoft/bayesianize
Bayesianize: A Bayesian neural network wrapper in pytorch
moucheng2017/Learn_Noisy_Labels_Medical_Images
[NeurIPS 2020] Disentangling Human Error from the Ground Truth in Segmentation of Medical Images
team-approx-bayes/fromp
Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
lxasqjc/Foveation-Segmentation
PyTorch implementation of Foveation for Segmentation of Ultra-High Resolution Images
1202kbs/Rectified-Gradient
Official repository for "Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps".
ahmedmalaa/discriminative-jackknife
Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.
fbragman/NiftyNet
An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy
Rokken-lab6/Failure-Analysis-and-Model-Repairment
rtanno21609/sgd-influence
Python codes for influential instance estimation