Improved Consistency Regularization for GANs
— roadrunner01 (@ak92501) February 13, 2020
pdf: https://t.co/IJki7WDD9T
abs: https://t.co/h1BPZ0KKWd pic.twitter.com/mDLyq1NbYS
Improved Consistency Regularization for GANs
— roadrunner01 (@ak92501) February 13, 2020
pdf: https://t.co/IJki7WDD9T
abs: https://t.co/h1BPZ0KKWd pic.twitter.com/mDLyq1NbYS
1 Million Fake Faces - 7 on #kaggle via @KaggleDatasets https://t.co/jwvu1IbDJq
— Bojan Tunguz (@tunguz) February 8, 2020
When AI > AI+human, we face important ethical questions.
— Alexandre Cadrin-Chênevert (@alexandrecadrin) February 7, 2020
"In the reader study, the performance level of AI was 0.940, significantly higher than that of the radiologists without AI assistance (0.810). With the assistance of AI, radiologists' performance was improved to 0.881." https://t.co/q16jpyJizU
Fixmatch: code for training on Imagenet dataset is released and available here:https://t.co/ees8y1fSt1https://t.co/ErAYUhZqTP
— Alexey Kurakin (@alexey2004) February 5, 2020
by Kihyuk Sohn @D_Berthelot_ML @chunliang_tw @ZizhaoZhang Nicholas Carlini @ekindogus @alexey2004 @Han_Zhang_ @colinraffel
New models from:
— Julien Chaumond (@julien_c) February 3, 2020
- @Wietsedv (Dutch BERT),
- @douwekiela at Facebook AI (MMBT, multi-modal model)
- @formiel, @laurent_besacie et al. (FlauBERT, French-trained XLM-like)
- @loretoparisi, @simofrancia et al. at @musixmatch (UmBERTo, Italian CamemBERT-like) pic.twitter.com/qgJ0fwqiwC
A well done video explanation of FixMatch, thanks @CShorten30 ! https://t.co/scOd1TIU3Q
— David Berthelot (@D_Berthelot_ML) January 31, 2020
Intro to anomaly detection with OpenCV, Computer Vision, and scikit-learn via @pyimagesearch https://t.co/CFxZBBsA9q #Python #OpenCV #ComputerVision #MachineLearning pic.twitter.com/MBj77NrZTx
— Python Weekly (@PythonWeekly) January 28, 2020
Kornia is a GPU accelerated computer vision library for @PyTorch.
— Jeremy Howard (@jeremyphoward) January 27, 2020
Link: https://t.co/XwrPrBczIY https://t.co/HMRNNcOQTj
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial Network
— roadrunner01 (@ak92501) January 23, 2020
pdf: https://t.co/QqIUyRJSpV
abs: https://t.co/olyFFQe4tT pic.twitter.com/RvrpGsZb8s
The quiet semisupervised revolution continues https://t.co/FAY4v9aHbe
— Ian Goodfellow (@goodfellow_ian) January 22, 2020
Code is up: https://t.co/mYFJdWwJaT
— David Berthelot (@D_Berthelot_ML) January 22, 2020
And being my usual distracted self, I forgot one co-author from the list: @alexey2004 (Sorry Alex!) The code for ImageNet will come later.
This is a very interesting paper. It shows that a tweaked ResNet50 is about as accurate as EfficientNet-B4 but >3x faster.
— Jeremy Howard (@jeremyphoward) January 21, 2020
The EfficientNet paper measured FLOPS, which is a theoretical performance measure, rather than time, which is what actually matters.https://t.co/Hzyokmf2x7 pic.twitter.com/cyBiueqPuf