@Machine_learn

An AI program that plays Flappy Bird using reinforcement learning.


Code: https://github.com/taivu1998/FlapAI-Bird

Model: https://stanford-cs221.github.io/autumn2019-extra/posters/18.pdf

Paper: https://arxiv.org/abs/2003.09579

Gradient boost trees with xgboost and scikit-learn #book #python
@Machine_learn

New paper by Yandex.MILAB 🎉
Tired of waiting for backprop to project your face into StyleGAN latent space to use some funny vector on it? Just distilate this tranformation by pix2pixHD!
arxiv.org/abs/2003.03581
@Machine_learn

@Machine_learn

Graph Isomorphism Software

Open-source software for finding isomorphism or canonical forms of graphs.

* Nauty/Traces
* Bliss
* saucy
* conauto
* Gi-ext

@Machine_learn
Train transformer language models with reinforcement learning.

https://lvwerra.github.io/trl/

Code: https://github.com/openai/lm-human-preferences

Paper: https://arxiv.org/pdf/1909.08593.pdf

@Machine_learn
Flows for simultaneous manifold learning and density estimation

A new class of generative models that simultaneously learn the data manifold as well as a tractable probability density on that manifold.

Code: https://github.com/johannbrehmer/manifold-flow

Paper: https://arxiv.org/abs/2003.13913

@Machine_learn

Gradient Centralization: A New Optimization Technique for Deep Neural Networks

Code: https://github.com/Yonghongwei/Gradient-Centralization

Paper: https://arxiv.org/abs/2004.01461

! pip install covid ‌
🦠
@Machine_learn

Artificial Vision and Language Processing for Robotics
#vision
#languageprocessing
#python
@Machine_learn

@Machine_learn

Advancing Self-Supervised and Semi-Supervised Learning with SimCLR

https://ai.googleblog.com/2020/04/advancing-self-supervised-and-semi.html

Code and Pretrained-Models: https://github.com/google-research/simclr

Papare: https://arxiv.org/abs/2002.05709

@Machine_learn

Deep unfolding network for image super-resolution

Deep unfolding network inherits the flexibility of model-based methods to super-resolve blurry, noisy images for different scale factors via a single model, while maintaining the advantages of learning-based methods.

Github: https://github.com/cszn/USRNet

Paper: https://arxiv.org/pdf/2003.10428.pdf

Python Data Visualization
Cookbook Second Edition
@Machine_learn

@Machine_learn

TVR: A Large-Scale Dataset for Video-Subtitle Moment Retrieval

Github: https://github.com/jayleicn/TVRetrieval


PyTorch implementation : https://github.com/jayleicn/TVCaption

Paper: https://arxiv.org/abs/2001.09099v1

@Machine_learn

PUBG Data Analysis
https://youtu.be/sah4m-9Il7o

@Machine_learn

Regularizing Meta-Learning via Gradient Dropout

Code: https://github.com/hytseng0509/DropGrad

Paper: https://arxiv.org/abs/2004.05859