1442 results for "replacements" across all locations
Innovative Recommendation Applications Using Two Tower Embeddings at Uber
Learn how we developed a unified, global, Two-Tower Embedding model to replace 1,035 city-specific DeepMF models, decreasing training time by orders of magnitude and working at Uber scale with millions of eaters and stores and hundreds of millions of items
#DecongestIndia has arrived
Outlines the potential impact of a movement called #DecongestDelhi which curbs causes of congestion in India
Introducing uberXL: The low cost SUV
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
Canberra Airport & Uber Rideshare Conditions and Standard Operating Procedures
Terms & Conditions
UberREPAIR is arriving now
Need some sort of car maintenance? Just choose UberREPAIR directly from the Uber app and help will come to your door
UberREPAIR is arriving now
Need some sort of car maintenance? Just choose UberREPAIR directly from the Uber app and help will come to your door
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
A. Nguyen, J. Clune, Y. Bengio, A. Dosovitskiy, J. Yosinski
Generating high-resolution, photo-realistic images has been a long-standing goal in machine learning. Recently, Nguyen et al. (2016) showed one interesting way to synthesize novel images by performing gradient ascent in the latent space of a generator network to maximize the activations of one or multiple neurons in a separate classifier network. In this paper we extend this method by introducing an additional prior on the latent code, improving both sample quality and sample diversity, leading to a state-of-the-art generative model that produces high quality images at higher resolutions (227×227) than previous generative models, and does so for all 1000 ImageNet categories. […] [PDF]
Computer Vision and Pattern Recognition (CVPR), 2017
Avoid fines of up to $1200 with a valid LAX placard
Following these pro tips will help you avoid fines between $200 and $1200 from LAX, so your pickups and dropoffs can be as smooth as possible.