population pyramids galore for #plotswithchristine
— Christine Zhang (@christinezhang) June 22, 2019
i noted here https://t.co/ljKDGXjjTj that DC's white population has an extreme 25-34yo bulge. compare that w/other races:
data&code: https://t.co/jS6eGJIHry, using #rstats+#python ⚡️ (median interpolation function ht @palewire) pic.twitter.com/QtKWBORo4F
Folks! I am finally not too embarrassed to re-release EasyGen, a visual programming language for text data pipelines for neural nets.
— Mark 🦑 Riedl (@mark_riedl) June 21, 2019
Colab: https://t.co/RvhFwfjJmx
Github: https://t.co/dmpbOav8So
Here’s a program to scrape the web for generating Star Trek/romance book titles. pic.twitter.com/yWHd7FiiZw
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time https://t.co/ymHvCJjC9y
— Python Trending (@pythontrending) June 17, 2019
Paper: https://t.co/V7U4FpYMb9
— Victor Zhong (@hllo_wrld) June 14, 2019
Dockerized code: https://t.co/gWocV5qmPn
10/10#nlproc#ACL2019NLP#DeepLearning
Can we use reinforcement learning together with search to solve temporally extended tasks? In Search on the Replay Buffer (w/ Ben Eysenbach and @rsalakhu), we use goal-conditioned policies to build a graph for search.
— Sergey Levine (@svlevine) June 13, 2019
Paper: https://t.co/qMEHyU06mU
Colab: https://t.co/jqADqWeJEu
Lots of requests to @seb_ruder & I for full replication details for ULMFiT on IMDb. Here it is! And thanks to @GuggerSylvain it now runs in just 6 hours on a single GPU :) https://t.co/xbl3pIcctD
— Jeremy Howard (@jeremyphoward) June 11, 2019
Deep Convolutional Networks as Shallow Gaussian Processes #iclr2019
— ML Review (@ml_review) June 3, 2019
By @AdriGarriga
The kernel equivalent to a 32-layer ResNet obtains 0.84% classification error on
MNIST, SoTA for GPs with comparable params size
Githubhttps://t.co/FBskmO4nqq
ArXivhttps://t.co/Xis40ncg29 pic.twitter.com/PD9aaE9ckd
EfficientNet-PyTorch - A PyTorch implementation of EfficientNet https://t.co/T2dstHaYPG
— Python Trending (@pythontrending) June 1, 2019
#Keras re-implementation of EfficientNet: https://t.co/8BEh92QIXE
— Alexandr Kalinin (@alxndrkalinin) May 31, 2019
- EfficientNet-B1 is 7.6x smaller and 5.7x faster on CPU inference than ResNet-152
- EfficientNet-B4 improves the top-1 accuracy from 76.3% of ResNet-50 to 82.6% (+6.3%), under similar FLOPS constraint pic.twitter.com/ZhQiDK8Itw
Realtime Coherent Style Transfer for Videos https://t.co/HDpMbikCGe #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch
— PyTorch Best Practices (@PyTorchPractice) May 30, 2019
We've open sourced a @Pytorch implementation of Augmented Neural ODEs 🌻 The repo contains tutorials and code to reproduce all experiments in the paper, including plots and gifs
— Emilien Dupont (@emidup) May 24, 2019
Github: https://t.co/HIiRDD3Ltw
Paper: https://t.co/awpQ3znNpW pic.twitter.com/y9n0zpApAo
Pytorch implementation of the MAC-Network https://t.co/PLxMiOzhGV #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch
— PyTorch Best Practices (@PyTorchPractice) May 23, 2019
