Popular GitHub Repositories for Gene Quantification

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

Lightweight, useful implementation of conformal prediction on real data.

Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

Python package for conformal prediction

Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

Open-source framework for uncertainty and deep learning models in PyTorch :seedling:

A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

RT-GENE: Real-Time Eye Gaze and Blink Estimation in Natural Environments

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]

Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning

A Python library for Gene–environment interaction analysis via deep learning

Training and evaluating a variational autoencoder for pan-cancer gene expression data

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

Conformal prediction for time-series applications.

A minimalist multi-agent framework for rubost automation of scientific analysis workflows, such as gene expression analysis.