aai-institute Goto Github PK

ai-kickstart-mlops

ai-sbom

AI Software Bill of Materials for EU AI Act

anomalib

A fork of the anomalib library for research purposes

beyond-jupyter

Software design principles for machine learning applications

capri-net

Code for CAPRI-Net

classwise-calibration-experiments

Experiments for the paper "Class-wise and reduced calibration methods", ICMLA 2022

configspace

Domain specific language for configuration spaces in Python/Cython. Useful for hyperparameter optimization and algorithm configuration.

continuiti

Learning function operators with neural networks.

continuity

continuity → continuiti

data-versioning-best-practices

gcp-mlflow-cloud-run

Example code for the tutorial on deploying serverless MLflow tracking in Google Cloud Run

gymnasium

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

kickstart_forests

kyle

A library for calibrating classifiers and computing calibration metrics

lakefs-spec

An fsspec implementation for the lakeFS project.

mlrc22-like-shapley-love-the-core

Code for the submission to the ML Reproducibility Challenge 2022, reproducing "If you like Shapley then you'll love the core"

mlstacks

A series of Terraform based recipes to provision popular MLOps stacks on the cloud.

nf4ad

Normalizing flows for anomaly detection

nnbench

A small framework for benchmarking machine learning models.

prototree

Fork of ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

pydata-hn

pydvl

pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation

rliable

[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.

sensai

The Python library for sensible AI.

shap-e

Generate 3D objects conditioned on text or images

skexgen

[ICML 2022] Official PyTorch Implementation of "SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks".

tfl-pydata2024-pydvl

The pyDVL slides for pyData Berlin 2024

tfl-training-probabilistic-model-checking

TfL course on probabilistic model checking using storm

tfl-training-rl

tfl-tumai-intro-rl

Repository with material for the RL workshop at TUM.AI