Search Results for author: Junjie Zhu

Found 6 papers, 2 papers with code

MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification

no code implementations17 Sep 2023 Junjie Zhu, Yiying Li, Chunping Qiu, Ke Yang, Naiyang Guan, Xiaodong Yi

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.

Data Augmentation Domain Adaptation +3

PVP: Pre-trained Visual Parameter-Efficient Tuning

no code implementations26 Apr 2023 Zhao Song, Ke Yang, Naiyang Guan, Junjie Zhu, Peng Qiao, Qingyong Hu

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)

Fine-Grained Image Classification

Network Enhancement: a general method to denoise weighted biological networks

no code implementations9 May 2018 Bo Wang, Armin Pourshafeie, Marinka Zitnik, Junjie Zhu, Carlos D. Bustamante, Serafim Batzoglou, Jure Leskovec

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

1 code implementation21 Mar 2017 Bo Wang, Daniele Ramazzotti, Luca De Sano, Junjie Zhu, Emma Pierson, Serafim Batzoglou

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.

Clustering Dimensionality Reduction

Unsupervised Learning from Noisy Networks with Applications to Hi-C Data

no code implementations NeurIPS 2016 Bo Wang, Junjie Zhu, Armin Pourshafeie, Oana Ursu, Serafim Batzoglou, Anshul Kundaje

In this paper, we propose an optimization framework to mine useful structures from noisy networks in an unsupervised manner.

Community Detection Denoising

Determination of the $WW$ polarization fractions in $pp \to W^\pm W^\pm jj$ using a deep machine learning technique

1 code implementation6 Oct 2015 Jacob Searcy, Lillian Huang, Marc-André Pleier, Junjie Zhu

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

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