1763 results for "airport" across all locations
uberBADD – Kolkata, let’s take the pledge against drunk driving!
uberBADD (Bars Against Drunk Driving) – a partnership with the top bars in Kolkata to fight against drunk driving. This collaboration, encouraged by the Kolkata Police, aims to help Kolkatans make smarter decisions when drinking on a night out.
Supporting Phoenix’s LGBT Community
Supporting Providence’s LGBT Community
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
N. Djuric, V. Radosavljevic, H. Cui, T. Nguyen, F.-C. Chou, T.-H. Lin, N. Singh, J. Schneider
We introduce an approach that takes into account a current world state and produces rasterized representations of each traffic actor’s vicinity. The raster images are then used as inputs to deep convnets to infer future movement of actors while also accounting for and capturing inherent uncertainty of the prediction task, with extensive experiments on real-world data strongly suggest benefits of the proposed approach. [PDF]
Winter Conference on Applications of Computer Vision (WACV), 2020
Matching Adversarial Networks
G. Mattyus, R. Urtasun
Generative Adversarial Nets (GANs) and Conditonal GANs (CGANs) show that using a trained network as loss function (discriminator) enables to synthesize highly structured outputs (e.g. natural images). However, applying a discriminator network as a universal loss function for common supervised tasks (e.g. semantic segmentation, line detection, depth estimation) is considerably less successful. […] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Few-Shot Learning Through an Information Retrieval Lens
E. Triantafillou, R. Zemel, R. Urtasun
Few-shot learning refers to understanding new concepts from only a few examples. We propose an information retrieval-inspired approach for this problem that is motivated by the increased importance of maximally leveraging all the available information in this low-data regime. [PDF]
Code: [LINK]
Advances in Neural Information Processing Systems (NeurIPS), 2017
Are you ready for an Uber Bachelorette Party?
Supporting Sacramento’s LGBT community
A chat about Ramadan with Uber partner-driver Feroj
Some tips for partner-drivers who are driving during Ramadan.
ES Is More Than Just a Traditional Finite-Difference Approximator
J. Lehman, J. Chen, Jeff Clune, Kenneth O. Stanley
An evolution strategy (ES) variant based on a simplification of a natural evolution strategy recently attracted attention because it performs surprisingly well in challenging deep reinforcement learning domains. It searches for neural network parameters by generating perturbations to the current set of parameters, checking their performance, and moving in the aggregate direction of higher reward. […] [PDF]
The Genetic and Evolutionary Computation Conference (GECCO), 2018