[2] Structured Matrix Scaling for Multi-Class Calibration (see also: experiments) [3] A Variational Estimator for Lp Calibration Errors (see also all experiments) [4] CalArena: A Large-Scale Post-Hoc ...
Abstract: In this paper, we present a novel deep metric learning method to tackle the multi-label image classification problem. In order to better learn the correlations among images features, as well ...
Neuroadaptive technologies are a type of passive Brain-computer interface (pBCI) that aim to incorporate implicit user-state information into human-machine interactions by monitoring ...
The ECO-SAM utilizes a pre-trained BERT encoder to obtain semantic embedding of input texts and then leverages a self-attention mechanism to model the semantic correlation between emotions.
Abstract: Multi-label classification (MLC) refers to the problem of tagging a given instance with a set of relevant labels. Most existing MLC methods are based on the assumption that the correlation ...
This repository contains the code and pretrained models for LS+: Informed Label Smoothing for Improving Calibration in Medical Image Classification, which has been accepted in MICCAI 2024. If the code ...
Anticancer peptides (ACPs), a series of short bioactive peptides, are promising candidates in fighting against cancer due to their high activity, low toxicity, and not likely cause drug resistance.
School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom National Biofilms Innovation Centre (NBIC) and Institute for Life ...
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