Joe Early's starred repositories
stable-diffusion
A latent text-to-image diffusion model
InvokeAI
InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
ai-deadlines
:alarm_clock: AI conference deadline countdowns
stablediffusion-infinity
Outpainting with Stable Diffusion on an infinite canvas
pytorch-fid
Compute FID scores with PyTorch.
awesome-RLHF
A curated list of reinforcement learning with human feedback resources (continually updated)
minDiffusion
Self-contained, minimalistic implementation of diffusion models with Pytorch.
UCR_Time_Series_Classification_Deep_Learning_Baseline
Fully Convlutional Neural Networks for state-of-the-art time series classification
InceptionTime
InceptionTime: Finding AlexNet for Time Series Classification
Conditional_Diffusion_MNIST
Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.
PaddleTS
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
arxiv-collector
A little Python script to collect LaTeX sources for upload to the arXiv.
minirocket
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
pytorch-timeseries
PyTorch implementations of neural networks for timeseries classification
InceptionTime-Pytorch
Unofficial Pytorch implementation of Inception layer for time series classification and its possible transposition for further use in Variational AutoEncoder
MILTimeSeriesClassification
Inherently Interpretable Time Series Classification via Multiple Instance Learning (MILLET)
pytorch-fid-wrapper
A simple wrapper around @mseitzer's great pytorch-fid work to compute Fréchet Inception Distance in-memory from batches of images, using PyTorch
MIL-Land-Cover-Classification
Code for the paper "Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification".
MIL-for-Non-Markovian-Reward-Modelling
Code for the paper "Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning".