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pyts

A Python package for time series classification

readme-template

README.md template for your open-source project

research-advice

articles about research and phd advice

rodrigob.github.com

my webpage at github.com

scenenetv1.0

Still a work in progress and adding code..

sds

Code for SDS

segnet-tutorial

Files for a tutorial to train SegNet for road scenes using the CamVid dataset

selfie-friendly-abstraction

Code repo for 'Learning Selfie-Friendly Abstraction from Artistic Style Images' (ACML 2018).

siamese-fc

State-of-the-art performance in arbitrary object tracking at 50-100 FPS with Fully Convolutional Siamese networks.

speciesdetection-21

sphereface

Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.

squeezenet

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters

squeezenet-residual

residual-SqueezeNet

styleguide

Style guides for Google-originated open-source projects

sunrgbd-meta-data

train test labels for sunrgbd

t-smart-tmux-session-manager

t - the smart tmux session manager

tandem

[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

tensor-puzzles

tensorflow

Computation using data flow graphs for scalable machine learning

tensorflow-deconvnet-segmentation

Tensorflow implementation of "Learning Deconvolution Network for Semantic Segmentation"

tensorflow-examples

TensorFlow Tutorial and Examples for beginners

tensorlayer

TensorLayer: A Deep Learning and Reinforcement Learning Library for TensorFlow.

tf-lift

Tensorflow port of LIFT (ECCV 2016), with training code.

tsia

Time series image analysis package

ultralytics

YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite

vim-pathogen

pathogen.vim: manage your runtimepath

vim-plug

:hibiscus: Minimalist Vim Plugin Manager

visdom

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

welcome_tutorials

Various tutorials given for welcoming new students at MILA.

wide_residual_nets_caffe

training wide residual networks in caffe