YoungJaeChoung

YoungJaeChoung's Stars

• AGI-Edgerunners/LLM-Planning-Papers

  Must-read Papers on Large Language Model (LLM) Planning.

  35018

• YoungJaeChoung/Presentation

  Presentation file (.PPT or .PDF)

  4

• Chia-Hsuan-Lee/KaggleDBQA

  Introduction page of a challenging text-to-SQL dataset: KaggleDBQA

  314

• YoungJaeChoung/mahalanobis

  mahalanobis by pytorch

  3

• YoungJaeChoung/pytorch_lstm_timeseries

  simple sample code to predict time series data (example: sine data)

  Language:Python22

• danielykim/flask-dash-minimal-app

  Minimal Dash App on Flask

  Language:Python3

• erdogant/distfit

  distfit is a python library for probability density fitting.

  Language:Jupyter Notebook36125

• bflammers/automahalanobis

  A PyTorch implementation of an autoencoder trained to minimize the Mahalanobis distance between input and reconstruction.

  Language:Python263

• AllenInstitute/coupledAE

  Repository for NeurIPS 2019 paper

  Language:Jupyter Notebook61

• carlosal1015/Books

  Math & Physics Books

  11335

• dsgissin/DiscriminativeActiveLearning

  Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For the blog:

  Language:Python20254

• ej0cl6/deep-active-learning

  Deep Active Learning

  Language:Python802184

• KlugerLab/SpectralNet

  Deep network that performs spectral clustering

  Language:Python320102

• dhaalves/CEAL_keras

  Implementation of "Cost-Effective Active Learning for Deep Image Classification" paper

  Language:Python3513

• ciortanmadalina/high_noise_clustering

  Techniques to cluster very noisy data (dropouts or random noise)

  Language:Jupyter Notebook6417

• RavenKyu/OpenTutorials_PyQt

  OpenTutorials 만들면서 배우는 PyQt 예제

  Language:Python11081

• seba-1511/lstms.pth

  PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

  Language:Python13624