mccrinbc
Engineering Physics Alum. Electrical Engineering at McMaster University.
McMaster UniversityHamilton, ON.
mccrinbc's Stars
mckinsey/causalnex
A Python library that helps data scientists to infer causation rather than observing correlation.
GPflow/GPflow
Gaussian processes in TensorFlow
cornellius-gp/gpytorch
A highly efficient implementation of Gaussian Processes in PyTorch
gpschool/gpss20
Gaussian Process and Uncertainty Quantification Summer School 2020
fepegar/torchio
Medical imaging toolkit for deep learning
fepegar/unet
"pip install unet": PyTorch Implementation of 1D, 2D and 3D U-Net architecture.
google/uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
lutzroeder/netron
Visualizer for neural network, deep learning and machine learning models
jeya-maria-jose/Medical-Transformer
Official Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" - MICCAI 2021
PV-Lab/BayesProcess
Physics informed Bayesian network + autoencoder for matching process / variable / performance in solar cells.
HarisIqbal88/PlotNeuralNet
Latex code for making neural networks diagrams
Project-MONAI/MONAI
AI Toolkit for Healthcare Imaging
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
google-research/robustness_metrics
Lightning-AI/pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
SamsungLabs/pytorch-ensembles
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020
IBM/spacetech-ssa
IBM Space Tech - Space Situational Awareness
floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
huggingface/pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
muellerzr/Practical-Deep-Learning-for-Coders-2.0
Notebooks for the "A walk with fastai2" Study Group and Lecture Series
aangelopoulos/conformal_classification
Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
MIC-DKFZ/nnUNet
PetarV-/TikZ
Complete collection of my PGF/TikZ figures.
OanaMariaCamburu/CanITrustTheExplainer
miguelvr/dropblock
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
uhlerlab/causaldag
Python package for the creation, manipulation, and learning of Causal DAGs
stanfordmlgroup/CheXaid
weinajin/anonymize-dicom
Python script to anonmyize dicom folder
google-research/arxiv-latex-cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
ericmjl/bayesian-analysis-recipes
A collection of Bayesian data analysis recipes using PyMC3