lttam Goto Github PK
Name: Tam Le
Type: User
Company: ISM
Bio: Assistant Professor at The Institute of Statistical Mathematics (ISM), Japan.
Name: Tam Le
Type: User
Company: ISM
Bio: Assistant Professor at The Institute of Statistical Mathematics (ISM), Japan.
Code for: "Adversarial Regression with Doubly Non-Negative Weighting Matrices" -- NeurIPS, 2021. (Tam Le*, Truyen Nguyen*, Makoto Yamada, Jose Blanchet, Viet Anh Nguyen)
Code for "Entropy Partial Transport with Tree Metrics: Theory and Practice" -- AISTATS 2021 (Tam Le & Truyen Nguyen)
Code and data for "Flow-based Alignment Approaches for Probability Measures in Different Spaces" -- AISTATS 2021 (Tam Le, Nhat Ho, Makoto Yamada)
Matlab code for generalized Aitchison embeddings (metric learning for histogram data points)
Code for "Generalized Sobolev Transport for Probability Measures on a Graph", published at ICML 2024 (Authors: Tam Le, Truyen Nguyen, Kenji Fukumizu)
Kmeans with flow-based tree Gromov-Wasserstein barycenters
Code for ECML/PKDD paper: "LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport"
Pen and paper exercises in machine learning
Compute Persistence Fisher distance (Fisher information metric between two persistence diagrams with and without Fast Gauss Transform) --- Algorithm 1 in Tam Le & Makoto Yamada NIPS'18
Official PyTorch implementation for paper: Sliced Wasserstein with Random-Path Projecting Directions
Code for "Optimal Transport for Measures with Noisy Tree Metric", published at AISTATS 2024 (Authors: Tam Le, Truyen Nguyen, Kenji Fukumizu)
Approximation path and optimal selection of regularization hyperparameter for some machine learning problems.
Code for "Scalable Counterfactual Distribution Estimation in Multivariate Causal Models", CLeaR 2024
Code for "Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics", published at AISTATS 2022 (Authors: Tam Le, Truyen Nguyen, Dinh Phung, Viet Anh Nguyen)
Matlab code for tree-Wasserstein distance in the paper "Tree-Sliced Variants of Wasserstein Distances", NeurIPS, 2019. (Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi) --- A valid positive definite Wasserstein kernel for persistence diagrams: exp(-TW/t)
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search at ICML2021
Code for "Scalable Unbalanced Sobolev Transport for Measures on a Graph", published at AISTATS 2023 (Authors: Tam Le, Truyen Nguyen, Kenji Fukumizu)
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🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
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Some thing interesting about visualization, use data art
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Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.