Search Results for author: Zhikai Chen

Found 13 papers, 5 papers with code

Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution

no code implementations25 Mar 2024 Zhikai Chen, Fuchen Long, Zhaofan Qiu, Ting Yao, Wengang Zhou, Jiebo Luo, Tao Mei

Technically, SATeCo freezes all the parameters of the pre-trained UNet and VAE, and only optimizes two deliberately-designed spatial feature adaptation (SFA) and temporal feature alignment (TFA) modules, in the decoder of UNet and VAE.

Denoising Image Super-Resolution +3

Neural Scaling Laws on Graphs

no code implementations3 Feb 2024 Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang

In this work, we delve into neural scaling laws on graphs from both model and data perspectives.

Graph Classification Link Prediction +1

Graph Foundation Models

no code implementations3 Feb 2024 Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang

Graph Foundation Model (GFM) is a new trending research topic in the graph domain, aiming to develop a graph model capable of generalizing across different graphs and tasks.

Label-free Node Classification on Graphs with Large Language Models (LLMS)

1 code implementation7 Oct 2023 Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang

In light of these observations, this work introduces a label-free node classification on graphs with LLMs pipeline, LLM-GNN.

Node Classification

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

2 code implementations7 Jul 2023 Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang

The most popular pipeline for learning on graphs with textual node attributes primarily relies on Graph Neural Networks (GNNs), and utilizes shallow text embedding as initial node representations, which has limitations in general knowledge and profound semantic understanding.

General Knowledge Node Classification

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

1 code implementation NeurIPS 2023 Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

Recent studies on Graph Neural Networks(GNNs) provide both empirical and theoretical evidence supporting their effectiveness in capturing structural patterns on both homophilic and certain heterophilic graphs.

Node Classification

Enhancing the Transferability of Adversarial Attacks via Scale Ensemble

no code implementations29 Sep 2021 Xianfeng Gao, Zhikai Chen, Bo Zhang

The experiments on ImageNet show that our method successfully mitigates the gap of transferability between models with different input sizes and achieves about 8% higher success rate comparing with the state-of-the-art input transformation methods.

MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes

no code implementations CVPR 2021 Zhikai Chen, Lingxi Xie, Shanmin Pang, Yong He, Bo Zhang

This paper presents MagDR, a mask-guided detection and reconstruction pipeline for defending deepfakes from adversarial attacks.

Appending Adversarial Frames for Universal Video Attack

no code implementations10 Dec 2019 Zhikai Chen, Lingxi Xie, Shanmin Pang, Yong He, Qi Tian

There have been many efforts in attacking image classification models with adversarial perturbations, but the same topic on video classification has not yet been thoroughly studied.

Classification General Classification +2

Unsupervised Single Image Deraining with Self-supervised Constraints

no code implementations21 Nov 2018 Xin Jin, Zhibo Chen, Jianxin Lin, Zhikai Chen, Wei Zhou

Most existing single image deraining methods require learning supervised models from a large set of paired synthetic training data, which limits their generality, scalability and practicality in real-world multimedia applications.

Benchmarking Generative Adversarial Network +1

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