Tag: w_code

Pytorch implementation of Octave convolution https://t.co/6Hygcy8A0W #pytorch #deeplearning #neuralnetwork

— PyTorch Best Practices (@PyTorchPractice) April 24, 2019

It's good to see that you don't always need to use ImageNet to do interesting research, when you can use MNIST, Fashion MNIST, K-MNIST, etc., in more creative ways. The GitHub repo to reproduce their experiments: https://t.co/3A8I60gnn6

— hardmaru (@hardmaru) April 24, 2019

Using Transformer models to generate Hacker News comments from titles.

Fun demo: https://t.co/pGfnObA9gX pic.twitter.com/j0YQIb3Uuu

— hardmaru (@hardmaru) April 23, 2019

Predicting future medical diagnoses with RNNs using Fast AI API from scratch
(full pytorch implementation of Doctor AI paper using Electronic Health Records) by @SparklePuleri https://t.co/a2wmQEQ7Cg

— Rachel Thomas (@math_rachel) April 22, 2019

New model zoo in @PyTorch for image segmentation by Pavel Yakubovskiy.https://t.co/IkkjRJyRIq

[1] UNet, FPN, PSPNet Heads
[2] Pre-trained backbones (30+) vgg, densenet, dpn, resnet, seresne(x)t, senet, inceptionresnetv2, etc
[3] Example on how to train on the CamVid dataset.

— Vladimir Iglovikov (@viglovikov) April 22, 2019

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019). https://t.co/17eVpoWT69 #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch

— PyTorch Best Practices (@PyTorchPractice) April 16, 2019

Pytorch implementation of Block Neural Autoregressive Flow https://t.co/6KGOSwLt9N #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch

— PyTorch Best Practices (@PyTorchPractice) April 16, 2019

Benchmarking Keras and PyTorch Pre-Trained Models. Very nicely done project.https://t.co/3wR1hz74gM

— Jeremy Howard (@jeremyphoward) April 11, 2019

Resnets 18, 34, 50, 101, and 152, with all the tweaks from the "Bag of Tricks" paper (and more), in one screen of @pytorch code ij @ProjectJupyter .

Took two days of refactoring to get to this point, but now it's *so* easy to tweak and see exactly what's going on. :) pic.twitter.com/L9HiIvDBTW

— Jeremy Howard (@jeremyphoward) April 7, 2019

PyTorch BigGraph: a distributed system for learning large graph embeddings
- up to billions of entities and trillions of edges
- Sharding and Negative Sampling
- WikiData embeddings (78 mil entities, 4131 relations)
- Blog: https://t.co/IcOitBBWxq
- Code: https://t.co/ESlTmDTwbB pic.twitter.com/jxoEagno1r

— PyTorch (@PyTorch) April 2, 2019

Free code for the #CausalInferenceBook in R, SAS, Stata, and Python.

Now updated and available through the book's web page.https://t.co/bRPFYazK2D

We are indebted to Roger Logan, @epiellie, Joy Shi, Sean McGrath, and James Fiedler. Thanks!#Rstats @Stata @SASsoftware @ThePSF

— Miguel Hernán (@_MiguelHernan) March 31, 2019

Finally! I have been awaiting a text->slide deck generator. An inevitable use of this tech.

Now we need slides->tldr and we can automate away 20% of corporate America. https://t.co/7jVj0DmDNX

— Hilary Mason (@hmason) March 27, 2019