Search Results for author:
Found 5 papers, 4 papers with code
Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral Analysis
Recent advances in prompt engineering enable large language models (LLMs) to solve multi-hop logical reasoning problems with impressive accuracy.
Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section
Recent advances in large language models have led to renewed interest in natural language processing in healthcare using the free text of clinical notes.
Predicting Blossom Date of Cherry Tree With Support Vector Machine and Recurrent Neural Network
Our project probes the relationship between temperatures and the blossom date of cherry trees.
Unfolded Deep Kernel Estimation for Blind Image Super-resolution
Nonetheless, the existing deep unfolding methods cannot explicitly solve the data term of the unfolding objective function, limiting their capability in blur kernel estimation.
Deep Convolutional Dictionary Learning for Image Denoising
Inspired by the great success of deep neural networks (DNNs), many unfolding methods have been proposed to integrate traditional image modeling techniques, such as dictionary learning (DicL) and sparse coding, into DNNs for image restoration.
