TrungTin Nguyen's repositories
blogdown
Create Blogs and Websites with R Markdown
bml-course
Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
BNP-GLLiM
This repository contains functions that are used for the BNP-GLLiM model in the preprint: "Bayesian nonparametric mixtures of experts for inverse problems".
computer-science
:mortar_board: Path to a free self-taught education in Computer Science!
CRPE-GMoE
About Code repository for: Nguyen, H., Nguyen, T., Nguyen, K., & Ho, N. (2024). Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, AISTATS 2024, Acceptance rate 27.6% over 1980 submissions.
CRPE-SGaME
Code repository for: Nguyen, H., Nguyen, T., & Ho, N. (2023). Demystifying Softmax Gating Function in Gaussian Mixture of Experts. NeurIPS 2023 Spotlight. The acceptance rate for spotlights and orals is 3.6%. Specifically, 67 orals and 378 spotlights were accepted out of 12343 submissions.
HyperRouter
Code for this paper "HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts via HyperNetwork". The 2023 Conference on Empirical Methods in Natural Language Processing. The acceptance rate for short papers is 14%. Specifically, out of 1041 submissions, 146 papers were accepted for the main conference.
NamsGLoME-Simulation
This repository contains all numerical experiments (R code) for "A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models". Electronic Journal of Statistics, 2022
CRPE-GMoE0
Code repository for: Nguyen, H., Nguyen, T., Nguyen, K., & Ho, N. (2024). Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, AISTATS 2024, Acceptance rate 27.6% over 1980 submissions.
dlwpt-code
Code for the book Deep Learning with PyTorch by Eli Stevens and Luca Antiga.
FLaMingos
Functional Latent datA Models for clusterING heterogeneOus curveS
google-research
Google AI Research
pytorch-Deep-Learning
Deep Learning (with PyTorch)
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
SaMUraiS
StAtistical Models for the UnsupeRvised segmentAion of tIme-Series
stat-learning
Notes and exercise attempts for "An Introduction to Statistical Learning"
texsupport.ims_cosponsored-ejs
LaTeX author support files for IMS co-sponsored journal EJS.