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Texas A&M University - College Station
- United States
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12:33
(UTC -05:00) - https://www.linkedin.com/in/shao-ting-chiu/
- https://orcid.org/0000-0002-9097-5623
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Multi-Joint dynamics with Contact. A general purpose physics simulator.
An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).
Fast Kolmogorov-Arnold Network in JAX, initial experiments
X-KANeRF [KANeRF-benchmarking]: KAN based NeRF with various basis functions like B-Splines, Fourier, Gaussians, Wavelets, Polynomials, etc
PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
Training small GPT-2 style models using Kolmogorov-Arnold networks.
Reservoir simulation in Julia: Multi-phase, multi-component Darcy flow based on Jutul.jl
Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning).
Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"
Data-driven and Physics-informed Operator Learning via Gaussian Processes
[ICML 2021] Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
Reference implementation for the Hasegawa-Wakatani model of plasma turbulence inside nuclear fusion reactors in two dimensions
Implementation of a Set Transformer in JAX from the paper 'Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks' by Lee et al. (2019)
The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University.
Pytorch implementation of set transformer
This is an unofficial implementation of the Point Transformer paper.
Python Notebook for a "geometric multigrid solver"
My course on multigrid methods at the University of Tennessee, Fall 2024
Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning
The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization
Our maintained PFN repository. Come here to train SOTA PFNs.