Code for the Deep k-Nearest Neighbors (DkNN) was just added to the #CleverHans model zoo: https://t.co/7T0xVX4HIw
— Nicolas Papernot (@NicolasPapernot) January 29, 2019
The paper describing this approach for estimating support for a test-time prediction within the training data is here: https://t.co/dIPb2jEaem pic.twitter.com/jVDFySZMnq
This is a cool Colaboratory notebook that shows how you can apply ML and NLP to the content of your own @feedly feeds.https://t.co/9RTmkiF539 pic.twitter.com/HqebWvl0AE
— Sebastian Ruder (@seb_ruder) January 28, 2019
Pytorch implementation of RA-retrofit https://t.co/iwaBgQs4tZ #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch
— PyTorch Best Practices (@PyTorchPractice) January 27, 2019
VAEs! Generating images with Tensorflow by Miguel Méndez https://t.co/8sKAaI3Q9Y #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #tensorflow
— TensorFlow Best Practices (@TFBestPractices) January 26, 2019
Amazing new application: paste the text of a programming problem in to the app, and it automatically suggests techniques to solve the problem.
— Jeremy Howard (@jeremyphoward) January 24, 2019
Uses ULMFiT and fastai/@PyTorch.https://t.co/Td8mqKKwzN
Desnapify: cool project about training a pix2pix-like model to remove Snapchat filters from pictures https://t.co/H2hWAQmBKM pic.twitter.com/rV9D4D4eL7
— François Chollet (@fchollet) January 14, 2019
Excited for the Transformer-XL codebase! It also extends my AWD-LSTM `https://t.co/F18vD0XbfY` script to download the One Billion Words + text8 datasets (original grabbed WikiText-2, WikiText-103, enwik8 and PTBC) whilst keeping the most important part ;)https://t.co/aWkksPxmdr pic.twitter.com/6UaO6O2BDh
— Smerity (@Smerity) January 11, 2019
They also released PyTorch and TF implementations with pretrained models: https://t.co/VrE2nR5wBY
— hardmaru (@hardmaru) January 11, 2019
REALLY cool improvement upon Transformer networks that makes use of recurrence and a relative positional encodings! Up to 1800x faster!
— Thomas Lahore (@evolvingstuff) January 10, 2019
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contexthttps://t.co/eV4iy1kOPT
TensorFlow & PyTorch: https://t.co/MqZAZKlhEn pic.twitter.com/TjrjOomYnb
PyTorch implementation of DRAW: A Recurrent Neural Network For Image Generation https://t.co/IzE8Mo4LhD #pytorch #draw #neuralnetworks
— PyTorch Best Practices (@PyTorchPractice) January 4, 2019
A Keras Implementation of Sketch-RNN! @Polly_zk trained his Keras model on the QuickDraw Guitar and Guitar+Cat classes which were not included in the official release. 🖍 https://t.co/Lasn7lDqUW pic.twitter.com/sCHbTTUH9I
— hardmaru (@hardmaru) January 4, 2019
I released PyTorch / TensorFlow / scikit-learn implementations of Fenchel-Young losses. The package is useful for probabilistic classification. Among distinguishing features, it supports outputting sparse probabilities and learning from label proportions. https://t.co/kmRX8phOqz pic.twitter.com/Lofzb1uTx6
— Mathieu Blondel (@mblondel_ml) January 2, 2019
