Search Results for author:
Found 6 papers, 2 papers with code
MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification
In order to tackle these issues, we turn to the recently proposed parameter-efficient tuning methods, such as VPT, which updates only the newly added prompt parameters while keeping the pre-trained backbone frozen.
PVP: Pre-trained Visual Parameter-Efficient Tuning
Large-scale pre-trained transformers have demonstrated remarkable success in various computer vision tasks.
Ranked #4 on
Image Classification
on VTAB-1k
(using extra training data)
Network Enhancement: a general method to denoise weighted biological networks
Networks are ubiquitous in biology where they encode connectivity patterns at all scales of organization, from molecular to the biome.
SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning
We here present SIMLR (Single-cell Interpretation via Multi-kernel LeaRning), an open-source tool that implements a novel framework to learn a sample-to-sample similarity measure from expression data observed for heterogenous samples.
Unsupervised Learning from Noisy Networks with Applications to Hi-C Data
In this paper, we propose an optimization framework to mine useful structures from noisy networks in an unsupervised manner.
Determination of the $WW$ polarization fractions in $pp \to W^\pm W^\pm jj$ using a deep machine learning technique
The unitarization of the longitudinal vector boson scattering (VBS) cross section by the Higgs boson is a fundamental prediction of the Standard Model which has not been experimentally verified.
High Energy Physics - Phenomenology High Energy Physics - Experiment
