GitXiv — Collaborative Open Computer Science

https://www.gitxiv.com/

"GitXiv is a space to share links to open computer science projects. Countless Github and arXiv links are floating around the web. Its hard to keep track of these gems. GitXiv attempts to solve this problem by offering a collaboratively curated feed of projects. Each project is conveniently presented as arXiv + Github + Links + Discussion. Users can submit their findings and let the community rank and discuss it. A regular newsletter makes it easy to stay up-to-date on recent advancements. It´s free and open."

@ArtificialIntelligenceArticles

Spectral Signatures in [Neural Net] Backdoor Attacks

paper: https://arxiv.org/abs/1811.00636

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing #emnlp2018

https://aclanthology.coli.uni-saarland.de/events/emnlp-2018#D18-1

Flow-based Deep Generative Models

Blog by Lilian Weng: https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html

"Writing Code for NLP Research" tutorial at #emnlp2018

Slides by the Allen Institute for Artificial Intelligence: https://docs.google.com/presentation/d/17NoJY2SnC2UMbVegaRCWA7Oca7UCZ3vHnMqBV4SUayc/e

45 years ago today TCP/IP was born
Paper by Vint Cerf & Bob Kahn describing a protocol for sending packets across networks: https://www.cs.princeton.edu/courses/archive/fall06/cos561/papers/cerf74.pdf

"Machine learning and artificial intelligence in the quantum domain"

By Vedran Dunjko, Hans J. Briegel: https://arxiv.org/abs/1709.02779

Democratizing the Promise of Artificial Intelligence 😍

AI Commons is an international nonprofit organization seeking to gather a true ecosystem to democratize access to AI capabilities, to allow anyone, anywhere to benefit from the possibilities that AI can provide.

WebSite: https://www.aicommons.com/

A Corpus for Reasoning About Natural Language Grounded in Photographs

Suhr et al.: https://arxiv.org/abs/1811.00491

GitHub: https://github.com/clic-lab/nlvr

Generating Memoji from Photos

Blog by Pat Niemeyer: https://patniemeyer.github.io/2018/10/29/generating-memoji-from-photos.html

Reinforcement Learning with Prediction-Based Rewards

By Yura Burda and Harri Edwards, OpenAI: https://blog.openai.com/reinforcement-learning-with-prediction-based-rewards/

Learning to Dress: Synthesizing Human Dressing Motion via Deep Reinforcement Learning
https://www.cc.gatech.edu/~aclegg3/projects/LearningToDress.html

FishExplorer

1.5 million neurons, cell-level activity during multiple behaviors
15 TB raw, 56 GB compressed
18 fish whole-brain data, ~100k neurons/fish

Data and code: https://github.com/xiuyechen/fishexplorer

Paper:https://www.sciencedirect.com/science/article/pii/S0896627318308444

#bigdata #brain #datascience #machinelearning #research

Unsolved Problems in AI

https://medium.com/ai-roadmap-institute/unsolved-problems-in-ai-38f4ce18921d @ArtificialIntelligenceArticles

Toward an AI Physicist for Unsupervised Learning

By Tailin Wu (MIT), Max Tegmark (MIT): https://arxiv.org/abs/1810.10525

#ArtificialIntelligence #ComputationalPhysics #DisorderedSystems

book : Deep Learning with JavaScript

by François Chollet , Shanqing Cai, Stanley Bileschi, Eric D. Nielsen https://livebook.manning.com/#!/book/deep-learning-with-javascript/welcome/v-1/0

Open Courses and Textbooks

By Samuel G. Finlayson: https://sgfin.github.io/learning-resources/

#artificialintelligence #bigdata #deeplearning #machinelearning #neuralnetworks

Simple, Distributed, and Accelerated Probabilistic Programming"

https://arxiv.org/abs/1811.02091
Code:https://github.com/google-research/google-research/tree/master/simple_probabilistic_programming/

"Quora Insincere Questions Classification"

Detect toxic content to improve online conversations

Kaggle: https://www.kaggle.com/c/quora-insincere-questions-classification

Driving Computer Vision with Deep Learning"

Blog: https://wayve.ai/blog/2018/10/8/vision-for-driving-with-deep-learning