FUNIT: Few-Shot Unsupervised Image-to-Image Translation

Code on GitHub:
https://bit.ly/2patFxh

Link to Paper:
https://lnkd.in/ekgDy5u

Link to Blog Post:
https://bit.ly/2JIm28n

#DataScience #MachineLearning #ArtificialIntelligence

✴️ @AI_Python_EN

Pytorch-Struct

Fast, general, and tested differentiable structured prediction in PyTorch. By Harvard NLP : https://lnkd.in/e2iGiNa

#PyTorch #DeepLearning #ArtificialIntelligence

✴️ @AI_Python_EN

Evaluating the Factual Consistency of Abstractive Text Summarization
https://lnkd.in/ewFMX8T

#ArtificialIntelligence #DeepLearning #NLP #NaturalLanguageProcessing

✴ @AI_Python_EN

PaperRobot: Incremental Draft Generation of Scientific Ideas
https://lnkd.in/exHGHjW

#ArtificialIntelligence #AI #MachineLearning #DeepLearning

❇ @AI_Python_EN

Look then Listen: Pre-Learning Environment Representations for Data-Efficient Neural Instruction Following

https://bit.ly/2Pn3PR4

#DataScience #MachineLearning #ArtificialIntelligence

✴ @AI_Python_EN

Deep learning hits mathematical theorem proofs

#deeplearning #artificialintelligence

https://arxiv.org/abs/1910.11797

❇ @AI_Python_EN

ICCV 2019 Best Papers Announced

https://medium.com/syncedreview/iccv-2019-best-papers-announced-27a1a21311e1


✴️ @AI_Python_EN

PipeDream: A new approach to parallelize DNN training with pipelining

#DataScience #MachineLearning #ArtificialIntelligence

https://bit.ly/32YHygq

✴️ @AI_Python_EN

Variational Temporal Abstraction

Taesup Kim, Sungjin Ahn, Yoshua Bengio

https://arxiv.org/pdf/1910.00775.pdf

#ActiveLearning #ArtificialIntelligence #DeepLearning

✴️ @AI_Python_EN

Bayesian Deep Learning Benchmarks

GitHub, by the Oxford Applied and Theoretical Machine Learning group

https://github.com/OATML/bdl-benchmarks

#Bayesian #DeepLearning

✴️ @AI_Python_EN

Neural Density Estimation and Likelihood-free Inference

George Papamakarios

https://arxiv.org/pdf/1910.13233.pdf

#Bayesian #NeuralDensityEstimation #Inference

✴️ @AI_Python_EN

Credit Risk Analysis Using #MachineLearning and #DeepLearning Models

Lovely paper by Peter Martey Addo, Dominique Guegan and Bertrand Hassani

Code on #Github (it's in #R)

https://github.com/brainy749/CreditRiskPaper

✴️ @AI_Python_EN

Very interesting paper where they solved the three-body problem using deep neural networks in a tremendously more computationally efficient manner. While there is a lot of talk about current deep learning not leading towards human-like intelligence, one must think more deeply as to all the fantastic areas, applications, and fields that current deep learning can be game-changing right now and can lead to a new era of human-machine collaboration.
#deeplearning
#solvingproblems

https://arxiv.org/abs/1910.07291

✴️ @AI_Python_EN

Facebook: Pushing state-of-the-art in 3D content understanding

#DataScience #MachineLearning #ArtificialIntelligence

https://bit.ly/2JBaYK5

✴️ @AI_Python_EN

A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models

https://arxiv.org/abs/1910.13148

#MachineLearning #neurips, #NeurIPS2019

✴️ @AI_Python_EN

How 20th Century Fox uses ML to predict a movie audience
Google Cloud Blog
https://bit.ly/2N3I7SC

#AI #DeepLearning #MachineLearning #DataScience

✴️ @AI_Python_EN