JAEarly

latextable

A Python library that adds Latex functionality to the Texttable package.

MIL-for-Non-Markovian-Reward-Modelling

Code for the paper "Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning".

MIL-Land-Cover-Classification

Code for the paper "Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification".

MIL-Manim

Multiple Instance Learning Animations with Manim.

MILLI

Code for the paper "Model Agnostic Interpretability for Multiple Instance Learning".

MILTimeSeriesClassification

Inherently Interpretable Time Series Classification via Multiple Instance Learning (MILLET)

Online-Style-Interpolator

An online deep learning image style interpolator.

EnsureCleanNotebooksAction

GitHub action for ensuring all Jupyter notebooks have clean metadata.

JAEarly/latextable

A Python library that adds Latex functionality to the Texttable package.

JAEarly/MILTimeSeriesClassification

Inherently Interpretable Time Series Classification via Multiple Instance Learning (MILLET)

JAEarly/MIL-Land-Cover-Classification

Code for the paper "Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification".

JAEarly/MILLI

Code for the paper "Model Agnostic Interpretability for Multiple Instance Learning".

JAEarly/Online-Style-Interpolator

An online deep learning image style interpolator.

JAEarly/MIL-for-Non-Markovian-Reward-Modelling

Code for the paper "Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning".

JAEarly/MIL-Manim

Multiple Instance Learning Animations with Manim.

JAEarly/bonfire

A backend library for multiple instance learning implemented in PyTorch.

JAEarly/MIL-Multires-EO

JAEarly/pygln

Python implementation of GLN in different frameworks

JAEarly/Reinforcement_Learning_An_Introduction_Ed2_Solutions

My solutions to the exercises in the second edition (2018) of Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto.

JAEarly/awesome-RLHF

A curated list of reinforcement learning with human feedback resources (continually updated)

JAEarly/bonfire-benchmark

JAEarly/composer

Supercharge Your Model Training

JAEarly/deep-neuroevolution

Deep Neuroevolution

JAEarly/DisasterRiskCompetition

JAEarly/heatmap.js

🔥 JavaScript Library for HTML5 canvas based heatmaps

JAEarly/JAEarly

JAEarly/KaggleActionsExample

A guide of how to interact with the Kaggle API via GitHub actions.

JAEarly/optuna

A hyperparameter optimization framework

JAEarly/PlotNeuralNet-MIL

Latex code for making Multiple Instance Learning (MIL) neural networks diagrams

JAEarly/pycatch22

python implementation of catch22

JAEarly/pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

JAEarly/pytorch-fid

Compute FID scores with PyTorch.

JAEarly/streaming

A Data Streaming Library for Efficient Neural Network Training

JAEarly/texttable

Python module for creating simple ASCII tables

JAEarly/the-turing-way

Host repository for The Turing Way: a how to guide for reproducible data science

JAEarly/tidytuesday

A collection of my Tidy Tuesday projects

JAEarly/vision

Datasets, Transforms and Models specific to Computer Vision

JAEarly/youCanCodeAGif

Can you make an High Quality Gif from A to Z only by coding? Yes. Do you want to, though?