junwoopark92

PyTorch-GAN

PyTorch implementations of Generative Adversarial Networks.

FinRL

FinRL: Financial Reinforcement Learning. 🔥

glide-text2im

GLIDE: a diffusion-based text-conditional image synthesis model

Autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

pytorch-ts

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

Anomaly-Transformer

About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

train-CLIP

A PyTorch Lightning solution to training OpenAI's CLIP from scratch.

FEDformer

OpenAI-CLIP

Simple implementation of OpenAI CLIP model in PyTorch.

pytorch-softdtw-cuda

Fast CUDA implementation of (differentiable) soft dynamic time warping for PyTorch

ts2vec

A universal time series representation learning framework

stochastic

Generate realizations of stochastic processes in python.

DILATE

Code for our NeurIPS 2019 paper "Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models"

EasyTemporalPointProcess

EasyTPP: Towards Open Benchmarking Temporal Point Processes

anomaly_transformer_pytorch

PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

DrRepair

[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages

Transformer-Hawkes-Process

Code for Transformer Hawkes Process, ICML 2020.

BIFI

[ICML 2021] Break-It-Fix-It: Unsupervised Learning for Program Repair

MICN

Code release of paper "MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting" (ICLR 2023)

neural_stpp

Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

STRIPE

Code for our NeurIPS 2020 paper "Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity"

ifl-tpp

Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)

NeuralWaveMachines

Official Implementation of the ICML 2023 paper: "Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks"

MetaST

MetaST for WWW 2019

Learning-Shapelets

A PyTorch implementation of learning shapelets from the paper Grabocka et al., „Learning Time-Series Shapelets“.

D3R

PyTorch implementation of "Drift doesn't Matter: Dynamic Decomposition with Dffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection" (NeurIPS 2023)

bnp

Pytorch implementation of neural processes and variants

neural_decomposition

Neaural Decomposition (ND)

TRUCE

Truth-Conditional Captions for Time Series Data. EMNLP 2021. Harsh Jhamtani, Taylor Berg-Kirkpatrick

Transformer-TCCT2021