kingofspace0wzz

a-PyTorch-Tutorial-to-Image-Captioning

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

academic-kickstart

capsule_attention

Deep-Semi-NMF

Theano-based implementation of Deep Semi-NMF.

Matrix-Analysis

A library for basic matrix computation and analysis

multilayer_nmf

My experiment of multilayer NMF, a deep neural network in which the first several layers take Semi-NMF as its pseudo-activation-function that finds the latent sturcture embedding in the original data unsupervisely.

paper

Papers that I read since 2019/3

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

wae-rnf-lm

Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399

zero123

Zero-1-to-3: Zero-shot One Image to 3D Object (ICCV 2023)

kingofspace0wzz/wae-rnf-lm

Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399

kingofspace0wzz/paper

Papers that I read since 2019/3

kingofspace0wzz/zero123

Zero-1-to-3: Zero-shot One Image to 3D Object (ICCV 2023)

kingofspace0wzz/ACE

Code for the paper, Neural Network Attributions: A Causal Perspective (ICML 2019).

kingofspace0wzz/AffineFlowCausalInf

Code for "Autoregressive flow-based causal discovery and inference" - ICML INNF workshop, 2020

kingofspace0wzz/babyagi

kingofspace0wzz/benchmark_VAE

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

kingofspace0wzz/causal-confusion

Code for paper Causal Confusion in Imitation Learning

kingofspace0wzz/computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

kingofspace0wzz/copula-vae-lm

kingofspace0wzz/cxplain

Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.

kingofspace0wzz/dag-learning

kingofspace0wzz/disentanglement-pytorch

Disentanglement library for PyTorch

kingofspace0wzz/disentangling-vae

Experiments for understanding disentanglement in VAE latent representations

kingofspace0wzz/Financial-Models-Numerical-Methods

Collection of notebooks about quantitative finance, with interactive python code.

kingofspace0wzz/gw_gan

Code for the Paper 'Learning Generative Models across Incomparable Spaces'

kingofspace0wzz/hsic-fair

kingofspace0wzz/kingofspace0wzz.github.io

Prince's academic webpage

kingofspace0wzz/lampe

Likelihood-free AMortized Posterior Estimation with PyTorch

kingofspace0wzz/latent-space-EBM-prior

kingofspace0wzz/NeuralDecomposition

PyTorch implementation of the paper "Neural Decomposition: Functional ANOVA with Variational Autoencoders"

kingofspace0wzz/NeurIPS19-SBDRL

Code for NeurIPS 2019 paper: "Symmetry-Based Disentangled Representation Learning requires Interaction with Environments" by H. Caselles-Dupré, M. Garcia-Ortiz and D. Filliat.

kingofspace0wzz/neurips2019_disentanglement_challenge_starter_kit

Starter Kit for the NeurIPS 2019 Disentanglement Challenge

kingofspace0wzz/photorama

"PHOTORAMA" template for Jekyll

kingofspace0wzz/proposals

Here stores some proposals I wrote in the past for my projects

kingofspace0wzz/python-tricks

Some cool Python tricks

kingofspace0wzz/the-art-of-command-line

Master the command line, in one page

kingofspace0wzz/torch-neuralpointprocess

(Pytorch ver) Code for "Fully Neural Network based Model for General Temporal Point Process"

kingofspace0wzz/ts_am

kingofspace0wzz/uai2020-fair

UAI2020 Fairness paper