JunYiShih

JunYiShih's Stars

• upscayl/upscayl

  🆙 Upscayl - #1 Free and Open Source AI Image Upscaler for Linux, MacOS and Windows.

  Language:TypeScript33.6k1658261.5k

• probml/pyprobml

  Python code for "Probabilistic Machine learning" book by Kevin Murphy

  Language:Jupyter Notebook6.6k1954561.6k

• lucidrains/vector-quantize-pytorch

  Vector (and Scalar) Quantization, in Pytorch

  Language:Python2.8k30137231

• MrNeRF/gaussian-splatting-cuda

  3D Gaussian Splatting, reimagined: Unleashing unmatched speed with C++ and CUDA from the ground up!

  Language:C952304476

• zll17/Neural_Topic_Models

  Implementation of topic models based on neural network approaches.

  Language:Jupyter Notebook42481877

• mattjj/svae

  code for Structured Variational Autoencoders

  Language:Python351271587

• Wanggcong/SparseNeRF

  [ICCV 2023] SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesis

  Language:Python27913348

• 3DOM-FBK/COLMAP_SLAM

  Visual-SLAM based on COLMAP API

  Language:Python266151028

• psanch21/VAE-GMVAE

  This repository contains the implementation of the VAE and Gaussian Mixture VAE using TensorFlow and several network architectures

  Language:Python207101132

• IntelLabs/CLNeRF

  Language:Python674910

• marc-rigter/polygrad-world-models

  Official code for "World Models via Policy-Guided Trajectory Diffusion", TMLR 2024

  Language:Python61402

• JunwenBai/C-GMVAE

  C-GMVAE: Gaussian Mixture VAE with Contrastive Learning for Multi-Label Classification

  Language:Python47249

• divymurli/VAEs

  Variational autoencoders: VAE, gaussian mixture VAE (GMVAE), and a basic ladder VAE (LVAE)

  Language:Jupyter Notebook462017

• HongtengXu/Relational-AutoEncoders

  Learning Autoencoders with Relational Regularization

  Language:Python45326

• emtiyaz/vmp-for-svae

  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)

  Language:Python445816

• db-Lee/Meta-GMVAE

  Language:Python39137

• wenxianxian/demvae

  Dispersed Exponential Family Mixture VAE

  Language:OpenEdge ABL27312

• yabozkurt/gmvae

  Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'

  Language:Jupyter Notebook20225

• eyounx/GANMM

  Mixture of Generative Adversarial Networks for Clustering

  Language:Python163110

• wangg12/vi_vae_gmm

  Variational Inference/Variational AutoEncoder + Gaussian Mixtures implementation in zhusuan

  Language:Python16316

• bhavikngala/gaussian_mixture_vae

  Language:Python13201

• bpucla/ibebm

  Language:OpenEdge ABL12213

• lupalab/ExNODE

  Exchangeable Neural ODE for Set Modeling

  Language:Python8220

• Lagergren-Lab/MixtureVAEs

  Repo for reproduction of the paper "Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders"

  Language:Python7100

• mazrk7/discvae

  A deep generative model that simultaneously clusters and disentangles latent representations of sequences.

  Language:Python7201

• JesperWestell/GMVAE_Experiments

  Experiments using Gaussian Mixture VAEs

  Language:Python6202

• millett/cs230_project

  CS230, Deep Learning, using VAE's and GMVAE's to characterize ICU data

  Language:Jupyter Notebook6314

• aciobanusebi/nf-mixture

  Language:Jupyter Notebook4200

• aalto-intelligent-robotics/bayesianfloorfield

  A novel approach to learn people flow able to combine knowledge about the environment geometry with observations from human trajectories

  Language:Python3101

• tlambert03/cmap

  Scientific colormaps for python, with only numpy dependency

  Language:Python1004