Yongchan Kwon

WeightedSHAP. WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)

UQ_BNN. Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)

DataInf. DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models (ICLR 2024)

beta_shapley. Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)

fast_dist_shapley. Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)

dataoob. Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value (ICML 2023)

wdro_local_perturbation. Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)

reasonIF. ReasonIF: Large Language Models Fail to Follow Instructions During Reasoning

LLM_TOM. What LLMs Think When You Don’t Tell Them What to Think About?

variational_autoencoder. variational_autoencoder

dagmm-1. A Pytorch implementation of the paper `Deep Autoencoding Gaussian Mixture Model For Unsupervised Anomaly Detection` by Zong et al.

valid-oversample. Valid Oversampling Schemes to Handle Imbalance

data_purchase_in_comp. Competition over data: how does data purchase affect users? (TMLR)

isles2017_deprecated. ISLES 2017 Theano-based code (deprecated!)

STAT5206_Spring_2023. Statistical Computing and Introduction to Data Science @ Columbia Stats

DataShapley. Data Shapley: Equitable Valuation of Data for Machine Learning

data-centric-ai. Resources for Data Centric AI

STAT5206_Fall_2022. Statistical Computing and Introduction to Data Science @ Columbia Stats

ykwon0407.github.io. Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

Influence_Subsampling. Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020

tcav. Code for the TCAV ML interpretability project

tf-vqvae. Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

pytorch_active_learning. PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book

Bayesian-Neural-Networks. Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace and more

learning-to-reweight-examples. PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning

MAML-Pytorch. Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

Policy-Gradients-Mulit-armed-Bandit-Problem. With the concept of Policy Gradients in Reinforcement Learning we are going find optimal policy for obtaining maximum reward in Multi-armed Bandit Problem

cs231_2015. Stanford cs231 2015 assignments

dpgmm. Dirichlet Process Gaussian Mixture Models

pytorch-tutorial. PyTorch Tutorial for Deep Learning Researchers

matching-networks-pytorch. Matching Networks for one shot learning

introtodeeplearning_labs. Lab Materials for MIT 6.S191: Introduction to Deep Learning

VIPS. Variational Inference by Policy Search