vincent05r Goto Github PK

comp5328-assignment2-test

Transition matrix estimators

dva-exp

Code release for "Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction" https://arxiv.org/abs/2309.00073

evac3d

fedformer-test

lstm_t1

testing & development for LSTM model

ltsf-linear

This is the adaptation of official implementation for AAAI-23 paper "Are Transformers Effective for Time Series Forecasting?"

neuralforecast

Scalable and user friendly neural :brain: forecasting algorithms.

nmt-seq2seq-attention

translation model using RNN + attension

nmt-transformer

non-negative-matrix-factorization---implemented-in-python

patchtst_test

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

pytorch-gan-lib

PyTorch implementations of Generative Adversarial Networks.

quant_crypto_frok_test

frok from a friend, simple strategy

real-esrgan

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

resnet_t-matrix_label-noise

using a transitional matrix to reduce the impact of label noise in supervised learning.

stable_diffusion_playground

Playing around with stable diffusion. Generated images are reproducible because I save the metadata and latent information. You can generate and then later interpolate between the images of your choice.

stock_models

using various machine learning models to predict stock prices

stock_models_transformer

t-revision

NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?

test_asm1_5328

Testing for COMP5328 assignment 1