TL;DR: Deep reinforcement learning (RL), a powerful learning framework to train AI agents, can be slow as it requires repeated interaction with a simulation of the environment. Our original WarpDrive accelerates multi-agent deep…
AUTHORS: Chenghao Liu, Quang Pham, Doyen Sahoo, Donald Rose TL;DR: Nonstationary data, which changes its statistical properties over time, can make time series forecasting difficult. Despite the recent success of deep learning techniques…
TL;DR: The performance of existing time-series forecasting methods can degrade due to non-stationarity, where the statistical distribution of time-series data changes over time. Our new DeepTime method overcomes non-stationarity issues by leveraging a…
AUTHORS: Zeyuan Chen, Ran Xu, Luyu Yang, Donald Rose TL;DR: Many methods designed to preserve online privacy propose complex security measures to protect sensitive data. We believe that not storing any sensitive data…
TL;DR: LAVIS (short for LAnguage-VISion) is an open-source deep learning library for language-vision research and applications, offering comprehensive support for a wide range of tasks, datasets, and state-of-the-art models. Featuring a unified interface…
TL;DR: We developed a new time-series forecasting model called ETSformer that leverages the power of two frameworks. By combining the classical intuition of seasonal-trend decomposition and exponential smoothing with modern transformers – as…
TL;DR: Salesforce Research and Mila announce AI for Global Climate Cooperation, a working group collaboration and competition to design negotiation protocols and climate agreements. We plan to coauthor a peer-reviewed scientific paper with…
