franciscoliu Goto Github PK

adversarylosslandscape

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]

bert-sda

covid-19-prediction.github.io

cs-103-pa01

cs-103-pa03

cs-103-pa2

cs103a-cpa01

customer_churning

Customer attrition or “churning” (i.e., more and more customers are leaving their credit card services, such as canceling the cards) is an important problem faced by credit card companies. In this project, you are given a dataset of 10,000 customers with 18 attributes/features, such as, age, salary, marital status, credit card limit, credit card category, and so on. The goal is to build a model that can accurately predict churning customers and help understand the reason behind the scene. The 5-fold cross-validation results will be used in evaluating the performance.

cv-auto-generator

detailed-virus-host.github.io

fairadj

Code for ICLR'2021 paper: On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections

franciscoliu

Config files for my GitHub profile.

franciscoliu.github.io

Zheyuan's Personal Website

gfame

Code for Paper fair graph representation learning via diverse mixture-of-experts, WWW 2023

grad-school-application

申请季材料汇总，给学弟学妹们提供一些参考。(PS, SOP, CV, etc.)

graphprompter

Implementation of GraphPrompter (The Web Conference 2024 Short Paper)

loss-landscape

Code for visualizing the loss landscape of neural nets

loss-landscapes

Approximating neural network loss landscapes in low-dimensional parameter subspaces for PyTorch

mixture-of-experts

PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538

semantic_indoor_seg

Sementation generation given the png image

serverless-pdf

simple-virus-host

sku

Official code implementation of SKU, Accepted by ACL 2024 Findings

starter-hugo-academic

vicky22birthday.github.io

zheyuanliu-personal-web