PyTorch Weekly
@PyTorchWeekly
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An in-depth look at the world of PyTorch. Sign up for our free weekly newsletter featuring curated news, articles and jobs related to PyTorch...
Joined July 2018
ICYMI, #PyTorch ~> Tutorial case study: Fixing your first PyTorch bug by @ThomasViehmann
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ICYMI, #PyTorch ~> PyTorch under the hood: a guide to understand PyTorch internals by @tarantulae
https://t.co/3ipovuwWtI
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ICYMI, #PyTorch ~> A selective excursion into the internals of PyTorch by @ThomasViehmann
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ICYMI, #PyTorch -> PyTorch image models, scripts, pre-trained weights: (SE)ResNet/ResNeXT, DPN, EfficientNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more by Ross Wightman https://t.co/ebtqHoEZaS
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ICYMI, #PyTorch -> PyTorch Binary Converter - turn PyTorch's floats into binary tensors and back by @karen_ullrich
https://t.co/uofhbm8q62
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11 mentors signed up for our #d3hack19 (sep 9-13, 2019)! Given we are capped to 9 teams, we'll have an ever increasing mentor ratio approaching 2 rapidly. @florianjug @fabian_theis @GuidoJuckeland @zih_tud @RSE_de @csbdresden Deadline is approaching: https://t.co/8N6mI9lDn9 RT!
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ICYMI, #PyTorch -> AdverTorch: A toolbox for adversarial robustness research by Gavin Weiguang Ding for @BorealisAI
https://t.co/9jGSAHOoz4
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ICYMI, #PyTorch -> Fine tuning for image classification using Pytorch by @abhi1thakur
https://t.co/jaKvESdUj6
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Announcing PyTorch Hub! Want ResNet, ResNext, BERT, GPT, PGAN, Tacotron, DenseNet, MobileNet...? - Pull models with 1 line of code. - Publish your models by sending a pull request. More info here:...
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We've compiled a meta-reading list for our meta-learning tutorial: https://t.co/3i5zohN4KM Short list of the main papers we covered in our meta-learning tutorial: https://t.co/g3eAcsO0vr
sites.google.com
Abstract In recent years, high-capacity models, such as deep neural networks, have enabled very powerful machine learning techniques in domains where data is plentiful. However, domains where data is...
@icmlconf @svlevine As requested by many, we compiled a list of references from the meta-learning tutorial here: https://t.co/z6R4jYcluH
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Hey everyone, I’m excited to announce “Efficient Adaptation of Pretrained Transformers for Abstractive Summarization,” a work by Andrew Hoang, myself, @real_asli and @YejinChoinka. https://t.co/mcdOXaAZvo 1/
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Have you heard about Bert? If you work in NLP you certainly have. I tried it for named entity recognition and wrote this blog post about it. Check it out! https://t.co/cnuULRGKoO
@PyTorch @PyTorchWeekly #DeepLearning
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A PyTorch implementation of "A Higher-Order Graph Convolutional Layer" (NeurIPS 2018). https://t.co/AL96bGOxzg
#MachineLearning #DeepLearning #PyTorch
@PyTorchPractice @learnpytorch @PyTorchWeekly @DeepLearningHub
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PyTorch implementation of DisturbLabel https://t.co/n0WhHyi9Ra a hidden gem from @CVPR 2016 @PyTorch @PyTorchPractice @PyTorchWeekly @machinelearn_d
#deeplearning #machinelearning #ai #pytorch #code #opensource #regularization
github.com
PyTorch implementation of DisturbLabel. Contribute to amirhfarzaneh/disturblabel-pytorch development by creating an account on GitHub.
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Just published a blog on using PyTorch C++ API for MNIST Digit Classification. Blog Link: https://t.co/CcOj6MNiSo Code: https://t.co/Ct6ZI2mV11
@PyTorchPractice @PyTorchWeekly @PyTorch #PyTorch #DeepLearning #ComputerVision
github.com
Implementing CNN for Digit Recognition (MNIST and SVHN dataset) using PyTorch C++ API - GitHub - krshrimali/Digit-Recognition-MNIST-SVHN-PyTorch-CPP: Implementing CNN for Digit Recognition (MNIST ...
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#PyTorch >>> Exploring Adversarial Reprogramming by the IIT Madras Computer Vision and Intelligence Group | https://t.co/XERm070KUL
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#PyTorch >>> Building a Neural Style Transfer app on iOS with PyTorch and CoreML by @alexiscreuzot | https://t.co/LPlXQYdm06
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#PyTorch >>> Neural Machine Translation With PyTorch - Tutorial 1: Encorder-Decoder by Anatolii Stehnii https://t.co/FwK0j5s507
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