Search Results for author:
Found 5 papers, 4 papers with code
Scaling Vision Transformers to 22 Billion Parameters
The scaling of Transformers has driven breakthrough capabilities for language models.
Ranked #1 on
Zero-Shot Transfer Image Classification
on ObjectNet
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes
We introduce UViM, a unified approach capable of modeling a wide range of computer vision tasks.
RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning
We introduce RLDS (Reinforcement Learning Datasets), an ecosystem for recording, replaying, manipulating, annotating and sharing data in the context of Sequential Decision Making (SDM) including Reinforcement Learning (RL), Learning from Demonstrations, Offline RL or Imitation Learning.
TensorFlow-Serving: Flexible, High-Performance ML Serving
We describe TensorFlow-Serving, a system to serve machine learning models inside Google which is also available in the cloud and via open-source.
BIG-bench Machine Learning
Vocal Bursts Intensity Prediction
Wide & Deep Learning for Recommender Systems
Memorization of feature interactions through a wide set of cross-product feature transformations are effective and interpretable, while generalization requires more feature engineering effort.
Ranked #2 on
Click-Through Rate Prediction
on Bing News
