As we issue our fourth Community Standards Report, we are sharing how recent advances in AI have helped us work more efficiently to keep people safe from harmful content across our platforms.

❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers

📝 The paper "Neural State Machine for Character-Scene Interactions" is available here:
https://github.com/sebastianstarke/AI4Animation

🙏 We would like to thank our generous…

MLPerf's new AI inference benchmarks gave top marks to NVIDIA Turing GPUs and Xavier SoCs.

The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.

An overview some ideas discussed at the Deep Learning for Visual SLAM Workshop at ICCV 2019.

What do pruned deep neural networks forget?

Official cleanlab repo is at https://github.com/cleanlab/cleanlab - cgnorthcutt/cleanlab

PyTorch code for our paper: Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? https://arxiv.org/abs/1908.09625 - Mrtn...

NeurIPS 2019: Learn to Move - Walk Around, 2nd place solution - GitHub - Scitator/run-skeleton-run-in-3d: NeurIPS 2019: Learn to Move - Walk Around, 2nd place solution

How to tune and optimize Prophet using domain knowledge to add greater control to your forecasts.

Posted by Florian Kainz and Kiran Murthy, Software Engineers, Google Research Taking pictures of outdoor scenes at night has so far been the dom...

Learn how we enable AR effects to fully interact with a scene geometry, for example, to enable occlusions by real objects in the scene.

Neural Graph Differential Equations (Neural GDEs). Contribute to Zymrael/gde development by creating an account on GitHub.

Most of us last saw calculus in school, but derivatives are a critical part of machine learning, particularly deep neural networks, which are trained by optimizing a loss function. This article is an attempt to explain all the matrix calculus you need in…

Our radar perception pipeline delivers 360-degree surround perception around the vehicle, using production-grade radar sensors operating at the 77GHz automotive microwave band.

gnn explainer. Contribute to RexYing/gnn-model-explainer development by creating an account on GitHub.

Jerome Pesenti is encouraged by progress in artificial intelligence, but sees the limits of the current approach to deep learning.