Lingkai Kong (Lingkai-Kong)

Lingkai-Kong

Geek Repo

Company:Harvard

Location:Cambridge

Home Page:lingkai-kong.com

Twitter:@konglingkai_AI

Github PK Tool:Github PK Tool

Lingkai Kong's repositories

SDE-Net

Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates

Language:PythonLicense:Apache-2.0Stargazers:104Issues:5Issues:12

Calibrated-BERT-Fine-Tuning

Code for Paper: Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data

Language:PythonLicense:Apache-2.0Stargazers:35Issues:3Issues:1

so-ebm

Code for paper: End-to-end Stochastic Optimization with Energy-based Model

Language:PythonStargazers:15Issues:2Issues:0
Language:PythonStargazers:2Issues:1Issues:0
Language:SCSSLicense:MITStargazers:0Issues:0Issues:0

avicenna

a minimal academic page for hugo

Language:HTMLLicense:MITStargazers:0Issues:1Issues:0

chempropBayes

Bayesian MPNNs for Molecular Property Prediction

Language:PythonLicense:MITStargazers:0Issues:1Issues:0
Language:ShellLicense:MITStargazers:0Issues:2Issues:0

Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Language:Jupyter NotebookLicense:NOASSERTIONStargazers:0Issues:1Issues:0

lda-c

This is a C implementation of variational EM for latent Dirichlet allocation (LDA), a topic model for text or other discrete data.

Language:CLicense:LGPL-2.1Stargazers:0Issues:1Issues:0
Language:PythonLicense:MITStargazers:0Issues:1Issues:0
Stargazers:0Issues:1Issues:0

MCMC

MCMC tutorial for the Local Group Astrostatistics workshop

Language:Jupyter NotebookLicense:MITStargazers:0Issues:1Issues:0

smc2017

Collected code and materials from the intensive course preparing for the workshop on Sequential Monte Carlo (SMC) methods at Uppsala University, August 2017

Language:Jupyter NotebookLicense:MITStargazers:0Issues:1Issues:0