intervention

stanfordnlp/pyvene

Stanford NLP Python library for understanding and improving PyTorch models via interventions

darrenjacoby/intervention

WordPress plugin to configure wp-admin and application state using a single config file.

LasseRafn/php-initial-avatar-generator

Generate avatars with initials from user names.

stanfordnlp/axbench

Stanford NLP Python library for benchmarking the utility of LLM interpretability methods

Intervention/image-laravel

Laravel Integration for Intervention Image

ctessier/nova-advanced-image-field

🌄 📐 A Laravel Nova advanced image field with cropping and resizing using Vue Advanced Cropper and Intervention Image

matriphe/laravel-imageupload

Upload image using Laravel's build in function and resize it automatically.

explanare/ravel

Evaluate interpretability methods on localizing and disentangling concepts in LLMs.

vingard/Tactical-Intervention-Revived

A maintained non-steam version of Tactical Intervention. Includes mod manager/support, loadouts, server browser and other features!

koriavinash1/BioExp

Explainability of Deep Learning Models

osiemsiedem/intervention-image-vips-driver

VIPS driver for Intervention Image.

getdave/wp-intervention

On-demand image manipulation for WordPress via the Intervention Library.

richardkwo/InvariantCausal.jl

Causal Inference with Invariant Prediction

antonlukin/poster-editor

Wrapper for PHP's GD Library for easy image manipulation. Support for scaling multi-line text, shapes, filters and smart resize.

healthbadge/episimmer

Episimmer is an Epidemic Simulation Framework for Decision Support. It is a highly flexible system that can be easily configured to help take decisions during an epidemic in closed communities like university campuses and gated communities.

cmkumar87/NUS-MOOC-Transacts-Corpus

An annotated corpus of discussion forum threads from Massive Open Online Courses.

Intervention/image-symfony

Symfony Integration for Intervention Image

DeanHazineh/Emergent-World-Representations-Othello

A mechanistic interpretability study invvestigating a sequential model trained to play the board game Othello

explanare/ood-prediction

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors

fabiantomischka/php-avatar-generator

Create colored avatars with letters in PHP

sergix44/imagezen

Image manipulation library

devdbrandy/iReporter

iReporter app enables users (citizen) to bring any form of corruption to the notice of appropriate authorities and the general public

Sanji515/Hackfest19

tariquedev/laravel-important-file

Laravel Framework Important Files

Gyrfalc0n/Projet-EMS-RP

Projet refait entièrement dans la v2 web

uzairakbar/causal-data-augmentation

Implementation for the NeurIPS 2025 paper: An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation

12pavani/Heart-Disesse-Prediction

Heart Disease Prediction Using Machine Learning is a logistic regression model that predicts heart disease based on medical data. It analyzes features like age and cholesterol, achieving 85.24% training accuracy and 80.49% testing accuracy, facilitating early detection for timely intervention.

chloevoyer/minds-at-work-adhd-rct

Reproducible codebase for my thesis on the Minds@Work-QWL (ADHD) intervention trial using linear mixed-effects modeling.

heinonmatti/baseline-visu

Describing and visualising baseline results of the Let's Move It intervention

hyemin-han/TensorFlow_Intervention

Predicting outcomes of educational interventions before investing in large-scale implementation efforts in school settings is essential for educational policy-making. However, due to time and resource limitations, conducting longitudinal, large-scale experiments testing outcomes of interventions in authentic settings is difficult. Here, we introduce the deep learning method as a way to address this issue and illustrate the use of the deep learning method for the prediction of intervention outcomes through a MATLAB implementation. The presented deep learning method extracts predictable patterns from an empirical dataset to simulate large-scale intervention outcomes. Findings from our simulations suggest that the deep learning applied simulation model can predict intervention outcomes significantly more accurately compared to the traditional regression analysis methods.

laorka/nf-x08-070

Ressources norme NF X08-070

lednhatkhanh/dtu-feedback-api

Luisibear98/intervention-jailbreak

This project explores methods to detect and mitigate jailbreak behaviors in Large Language Models (LLMs). By analyzing activation patterns—particularly in deeper layers—we identify distinct differences between compliant and non-compliant responses to uncover a jailbreak "direction." Using this insight, we develop intervention strategies that modify

Rafkev/equitypadi

EquityPadi was a tool developed to share government intervention fund equitably, based on some considered criteria within a local government in Lagos state, Nigeria

rmartosprieto/chloroDAG

Causal inference of post-transcriptional regulation timelines from long-read sequencing in Arabidopsis thaliana