PatchFM is a basic model for univariate time series forecasting based on the Transformer architecture. It uses a block-by-block forecasting method, drawing on the training ideas of large language models to divide the time series into blocks for next-block forecasting. It supports multi-quantile output and uncertainty estimation.

Scientific ComputingSafetensors

A diffusion model-based video frame interpolation tool supporting multi-frame input with uncertainty estimation

Computer VisionSafetensorsEnglish

This is a quantile forest-based regression model for predicting California housing prices and providing uncertainty estimates.

Scientific ComputingScikit-learn

URM-LLaMa-3.1-8B is an uncertainty-aware reward model designed to enhance the alignment of large language models.

Natural Language ProcessingSafetensors

RT-DETR is the first real-time end-to-end object detector, achieving 53.1% AP and 108 FPS on the COCO dataset through an efficient hybrid encoder and uncertainty-minimized query selection mechanism.

Computer VisionTransformersEnglish

Fine-tuned based on the BERTweet foundation model for detecting linguistic uncertainty (hedging) in social media texts.

Natural Language ProcessingTransformersEnglish

A BERT-based multi-category uncertainty cue recognition model capable of detecting four different types of uncertainty cues at the token level.

Natural Language ProcessingTransformersEnglish