Agustinus Kristiadi (@wiseodd)
github

wiseodd

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Top repositories

1

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Python
7,304
star
2

MCMC

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Python
356
star
3

hipsternet

All the hipster things in Neural Net in a single repo
Python
287
star
4

controlled-text-generation

Reproducing Hu, et. al., ICML 2017's "Toward Controlled Generation of Text"
Python
241
star
5

probabilistic-models

Collection of probabilistic models and inference algorithms
Python
241
star
6

natural-gradients

Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)
Python
135
star
7

last_layer_laplace

Last-layer Laplace approximation code examples
Jupyter Notebook
78
star
8

cnn-levelset

Source code for Kristiadi and Pranowo, 2017's "Deep Convolutional Level Set Method for Image Segmentation"
Python
59
star
9

pub-ready-plots

Agustinus' very opiniated publication-ready plotting library
Python
50
star
10

wiseodd.github.io

Agustinusโ€˜ personal website and blog
MDX
39
star
11

lula

Companion code for the paper "Learnable Uncertainty under Laplace Approximations" (UAI 2021).
Python
18
star
12

compound-density-networks

Implementation of: Kristiadi, Agustinus, and Asja Fischer. "Predictive Uncertainty Quantification with Compound Density Networks." (2019).
Python
15
star
13

lapeft-bayesopt

Discrete Bayesian optimization with LLMs, PEFT finetuning methods, and the Laplace approximation.
Python
14
star
14

cuda-pso

Comparison between CUDA and CPU for PSO using 3-dimensional Levy function as test case
C++
13
star
15

bayesian_ood_training

Jupyter Notebook
9
star
16

swarm-image-segmenter

Image segmentation using swarm intelligence, accelerated using GPGPU (CUDA)
C++
7
star
17

laplace-bayesopt

Laplace approximated BNN surrogate for BoTorch
Python
7
star
18

phd_thesis_template

TeX
4
star
19

rgpr

Companion code for the paper "An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence" (NeurIPS 2021)
Python
4
star
20

two-funds-rebalancer

Given your current portfolio value, desired allocation after rebalancing, and the amount of cash you have, this script will output how much of your cash should be used to buy stock/bonds (in percent). Only works for portfolios with two funds, e.g. the Couch Potato and classic two-funds 60-40 portfolios.
Python
2
star
21

llm-bayesopt-exps

Official experiment code for the "Sober Look at LLMs for Material Discovery" paper.
Python
1
star
22

bo-async-feedback

Python
1
star