Facebook open sourced video alignment algorithms that detect identical and near identical videos to build more robust defenses against harmful visual content.

Project page: https://newsroom.fb.com/news/2019/08/open-source-photo-video-matching/
Code: https://github.com/facebookresearch/videoalignment

#Facebook #video #cv #dl

ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.

​​New paper on training with pseudo-labels for semantic segmentation

Semi-Supervised Segmentation of Salt Bodies in Seismic Images:
SOTA (1st place) at TGS Salt Identification Challenge.

Github: https://github.com/ybabakhin/kaggle_salt_bes_phalanx
ArXiV: https://arxiv.org/abs/1904.04445

#GCPR2019 #Segmentation #CV

​​Long-form question answering

Facebook AI shared the first large-scale data set, code, and baseline models for long-form QA, which requires machines to provide long, complex answers — something that existing algorithms have not been challenged to do before.

Link: https://ai.facebook.com/blog/longform-qa/

#FacebookAI #Facebook #NLP #NLU #QA

PyTorch for research

PyTorch Lightning — The PyTorch Keras for ML researchers. More control. Less boilerplate.

Github: https://github.com/williamFalcon/pytorch-lightning

#PyTorch #Research #OpenSource

spaCy meets PyTorch-Transformers: Fine-tune BERT, XLNet and GPT-2

Including pretrained models.

Link: https://explosion.ai/blog/spacy-pytorch-transformers
Pip: pip install spacy-pytorch-transformers

#Transformers #SpaCy #NLP #NLU #PyTorch #Bert #XLNet #GPT

ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.

You do not need any presentation or preparation, this is free format for people who are around these days and wanna chat with fellow data scientists

​​Photo to anime portrait

U-GAT-IT — Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation.

Link: https://github.com/taki0112/UGATIT

#Tensorflow #GAN #CV #DL #anime

​​Unified rational protein engineering with sequence-only deep representation learning

UniRep predicts amino-acid sequences that form stable bonds. In industry, that’s vital for determining the production yields, reaction rates, and shelf life of protein-based products.

Link: https://www.biorxiv.org/content/10.1101/589333v1.full

#biolearning #rnn #Harvard #sequence #protein

A Guide for Making Black Box Models Explainable.

One of the biggest challenges is to make ML models interpretable (explainable to human, preferably, non-expert). It matters not only in terms of credit scoring, to exclude possibility of racism or any other bias or news promotion and display (Cambridge Analytica case), but even in terms of debug and further progress in model training.


Link: https://christophm.github.io/interpretable-ml-book/

#guide #interpretablelearning #IL

🔥 New Releases: PyTorch 1.2, torchtext 0.4, torchaudio 0.3, and torchvision 0.4

https://pytorch.org/blog/pytorch-1.2-and-domain-api-release/

https://github.com/pytorch/pytorch/releases

​​Simple real time visualisation of the execution of a #python program: https://github.com/alexmojaki/heartrate

T-shirt to inject junk data into surveillance systems. Stylish tool for peaceful protest against state human tracking
🔎 adversarialfashion.com
📉 @loss_function_porn

Community Day @ MLSS 2019

MLSS Community Day is a free one-day event for everyone interested in Machine Learning.

Speakers from premier institutions in Machine Learning such as the University of Oxford, University College London, Max Planck Institute as well as renowned companies will cover the latest advances in applications for healthcare, telecommunications, NLP, finance, and quantum computing.

When & Where: August 31, Skoltech, Moscow
Link: https://mlss2019.skoltech.ru/community-day

#MLSS #MLSS2019 #Skolkovo

DeepMind's Behaviour Suite for Reinforcement Learning

DeepMind released Behaviour Suite for Reinforcement Learning, or ‘bsuite’ – a collection of carefully-designed experiments that investigate core capabilities of RL agents.

bsuite was built to do two things:

1. Offer clear, informative, and scalable experiments that capture key issues in RL
2. Study agent behaviour through performance on shared benchmarks

GitHub: https://github.com/deepmind/bsuite
Paper: https://arxiv.org/abs/1908.03568v1
Google colab: https://colab.research.google.com/drive/1rU20zJ281sZuMD1DHbsODFr1DbASL0RH

#RL #DeepMind #Bsuite

Neural Text d̶e̶Generation with Unlikelihood Training

Introducing a new objective, unlikelihood training, which forces unlikely generations to be assigned lower probability by the model, which improves overall quality of generated text.

Link: https://arxiv.org/pdf/1908.04319.pdf

#NLU #NLP #textgeneration

ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.

​​🥇Parameter optimization in neural networks.

Play with three interactive visualizations and develop your intuition for optimizing model parameters.

Link: https://www.deeplearning.ai/ai-notes/optimization/

#interactive #demo #optimization #parameteroptimization #novice #entrylevel #beginner #goldcontent #nn #neuralnetwork

The HSIC Bottleneck: Deep Learning without Back-Propagation

An alternative to conventional backpropagation, that has a number of distinct advantages.

Link: https://arxiv.org/abs/1908.01580

#nn #backpropagation #DL #theory