mlwscv2002

Welcome to the Duke Machine Learning Winter School: Computer Vision 2022!

The MLWS-CV includes 3 hands-on training sessions on implementing machine learning tools with the PyTorch software platform. You can see the full description at https://plus.datascience.duke.edu/mlwscv2022

Day 1: Introduction to PyTorch (Billy Carson)

Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day1_student_notebook.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day1_solution_notebook.ipynb

Day 2: Pytorch for image analysis with convolutional neural networks (Gavin Karr)

Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day2_student_notebook.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day2_solution_notebook.ipynb

Day 3: PyTorch for image analysis including image segmentation and object detection (Akhil Ambekar)

Part 1:
Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day3_student_notebook_part1.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day3_solutions_notebook_part1.ipynb

Part 2:
Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day3_student_notebook_part2.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day3_solutions_notebook_part2.ipynb

We are using a virtual computing environment provided by Duke's Office of Information Technology (OIT). For those that are interested, the source code for the Docker container can be found here: https://gitlab.oit.duke.edu/mccahill/ml-winter-school

Duke Machine Learning Winter School: Computer Vision 2022

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Overview

mlwscv2002

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Duke + Data Science (+DS)

Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021.

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation, CVPR2022

Automatically replace ONNX's RandomNormal node with Constant node.

Code for "Localization with Sampling-Argmax", NeurIPS 2021

EEGEyeNet is benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty

Scalable Optical Flow-based Image Montaging and Alignment

Extremely simple and fast extreme multi-class and multi-label classifiers.

Code for "Offline Meta-Reinforcement Learning with Advantage Weighting" [ICML 2021]

RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition

SPRING is a seq2seq model for Text-to-AMR and AMR-to-Text (AAAI2021).

Code for "Adversarial attack by dropping information." (ICCV 2021)

Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset

Improving Factual Consistency of Abstractive Text Summarization

Implementation for NeurIPS 2021 Submission: SparseFed

Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]

GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.

A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.

Pytorch implementation of FlowNet by Dosovitskiy et al.

exponential adaptive pooling for PyTorch

PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)