Skip to content Skip to sidebar Skip to footer

All Posts

Viewing 577-584 posts
Machine Learning

This AI Paper Introduces the Diffusion World Model (DWM): A General Framework for Leveraging Diffusion Models as World Models in the Context of Offline Reinforcement learning

Reinforcement learning (RL) comprises a wide range of algorithms, typically divided into two main groups: model-based (MB) and model-free (MF) methods. MB algorithms rely on predictive models of environment feedback, termed world models, which simulate real-world dynamics. These models facilitate policy derivation through action exploration or policy optimization. Despite their potential, MB methods often need…
March 4, 20240Likes0Comments
Machine Learning

Researchers from CMU and NYU Propose LLMTime: An Artificial Intelligence Method for Zero-Shot Time Series Forecasting with Large Language Models (LLMs)

Despite having some parallels to other sequence modeling issues, like text, audio, or video, time series has two characteristics that make it particularly difficult. Aggregated time series datasets frequently include sequences from drastically varied sources, occasionally with missing values, in contrast to video or audio, which normally have uniform input scales and sample rates. Furthermore,…
March 4, 20240Likes0Comments
Newest posts Older posts