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GrainSack

I'm stduy about ML and Deep learning theory and Mathematics

I am also studying applications, but I am mainly interested in theoretical fields.

I am studying mathematical learning methods for artificial intelligence models and more advanced models or effective analysis based on them.

Studied about Graph theory, Harmonic analysis, optimal bounded theory, Neural tangent kernel theory, recommendation system, dimensionality reduction, diffusion system, generative model, NLP, CV etc...


I am going to graduate from Yonsei University with a master's degree in math and calculation.

If you have any questions about personal contact or research, please email us.

[email protected]

grainsack's Projects

autobound icon autobound

AutoBound automatically computes upper and lower bounds on functions.

ddim icon ddim

Denoising Diffusion Implicit Models

distill_cf icon distill_cf

Data distillation for recommender systems. Shows equivalent performance with 2-3 orders less data.

grainsack.github.io icon grainsack.github.io

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

hyperbolic-learning icon hyperbolic-learning

Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)

infinite_ac_cf icon infinite_ac_cf

[ NeurIPS '22 ] ∞-AE model's implementation in JAX. Kernel-only method outperforms complicated SoTA models with a closed-form solution and a single hyper-parameter.

neural-tangent-transfer icon neural-tangent-transfer

Code accompanying our paper "Finding trainable sparse networks through Neural Tangent Transfer" to be published at ICML-2020.

neural_cf icon neural_cf

neural collaborative filtering tensorflow 2.0

nsmc icon nsmc

Naver sentiment movie corpus

pixellib icon pixellib

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

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