Pinned Repositories
cadgan
ICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.
fsic-test
ICML 2017. Kernel-based adaptive linear-time independence test.
interpretable-test
NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
jtcc
Java library to tokenize Thai text into a list of TCCs
k2abc
AISTATS 2016. K2-ABC: Approximate Bayesian Computation with Kernel Embeddings.
kernel-cgof
UAI 2020. Kernel goodness-of-fit tests for conditional density models.
kernel-ep
UAI 2015. Kernel-based just-in-time learning for expectation propagation
kernel-gof
NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
kernel-mod
NeurIPS 2018. Linear-time model comparison tests.
l1lsmi
squared-loss mutual information based feature selection
wittawatj's Repositories
wittawatj/kernel-gof
NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
wittawatj/interpretable-test
NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
wittawatj/cadgan
ICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.
wittawatj/kernel-ep
UAI 2015. Kernel-based just-in-time learning for expectation propagation
wittawatj/kernel-mod
NeurIPS 2018. Linear-time model comparison tests.
wittawatj/fsic-test
ICML 2017. Kernel-based adaptive linear-time independence test.
wittawatj/kernel-cgof
UAI 2020. Kernel goodness-of-fit tests for conditional density models.
wittawatj/k2abc
AISTATS 2016. K2-ABC: Approximate Bayesian Computation with Kernel Embeddings.
wittawatj/GAN_stability
Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"
wittawatj/awesome-mlss
List of summer schools in machine learning + related fields across the globe
wittawatj/cmdprod
Automatically generate command-line arguments for parameter sweeping
wittawatj/configs
my Linux configuration files
wittawatj/mlss2020-code
Code for backend processing of MLSS 2020, Tuebingen http://mlss.tuebingen.mpg.de/2020/
wittawatj/model-comparison-test
NeurIPS 2019. Kernel Stein Tests for Multiple Model Comparison.
wittawatj/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
wittawatj/test-sphinx
wittawatj/bam-read-count
wittawatj/i3-gnome
Use i3 with GNOME Session integration.
wittawatj/igms
Implicit generative models and related stuff based on the MMD, in PyTorch
wittawatj/independent-jobs
Python framework for independent computation with backends for batch clusters
wittawatj/jekyll-jupyter-notebook2
wittawatj/l1_two_sample_test
wittawatj/maf
Masked Autoregressive Flow
wittawatj/mltrain-nips-2017
This repository contains all the material for the MLTrain NIPS workshop
wittawatj/PerceptualSimilarity
Learned Perceptual Image Patch Similarity (LPIPS) metric. In CVPR, 2018.
wittawatj/pytorch-mdn
Mixture Density Networks for PyTorch
wittawatj/pytorch-summary
Model summary in PyTorch similar to `model.summary()` in Keras
wittawatj/sab2019_learnalgo
SAB 2019 at the MPI-IS EI department. "Learning algorithms overview poster
wittawatj/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
wittawatj/wj-jupyter-notebook-theme
Personal theme that I use for iPython notebooks