🔍 AI Model Identity Fingerprinting Tool - Verify AI model identity through self-Q&A | AI 模型身份指纹识别工具 - 通过自问自答验证模型真实身份

Daline: A Data-driven Power Flow Linearization Toolbox for Power Systems Research and Education

Data-driven Battery Model Identification in LPV Framework using Python

Code for our paper Demand Response Model Identification and Behavior Forecast with OptNet: a Gradient-based Approach.

Model Parameter Identification via a Hyperparameter Optimization Scheme (MI-HPO)

Advanced Data Assimilation Algorithms and Methods

A powerful, no code solution for control and systems engineering

Performed a nonlinear model identification using both the FROE method with polynomial NARX models and feedforward neural networks.

A skill to make agents search for better models

Data repository of the work published in Huber et al. 2026.

Filtered Sequential Monte Carlo for time-varying model parameters analysis

Lecture notes of the course Model Identification and Data Analysis - Part 2, Politecnico di Milano, A.Y. 2021-2022.

PAMELA 行为指纹识别系统：基于单 token 输出分布的 Jensen-Shannon Divergence 度量，识别 LLM API 真实身份。内置 173 个模型参考指纹库（涵盖 OpenAI/Anthropic/Google/Meta/Qwen/DeepSeek/GLM/Mistral/Moonshot/Llama/Nvidia/Amazon/Nous/Cohere/ByteDance 等 30+ 厂商），工具无关——任何能调 LLM API 的客户端（curl/Python/浏览器/Hermes/OpenClaw/Codex）都能采集。Apache-2.0/MIT/CC-BY-4.0

Lecture notes of the course Model Identification and Data Analysis - Part 1, Politecnico di Milano, A.Y. 2021-2022.

Grey box optimization of a UAV drone system with Matlab and Simulink & Robustness Monte-Carlo analysis on signal excitation

Scry what model is really behind that endpoint. Open signature format and self-service tool to verify that an LLM endpoint serves the declared model and precision, with an optional community registry for model identification.

Identify which LLM produced given answers — based on single-token behavioral fingerprints (Bruckner 2026, arXiv:2607.10252). 170 models, 10 tasks, 4 languages.

Matlab codes for analyzing and designing single-cell experiments.

Model identifiability pipeline using surrogate models trained on a latent space extracted by tensor decompositions.

This repository contains all GAMS files related to a 4th year research project based at Imperial College London focusing on the formulation of a new MIQCQP approach to symbolic polynomial regression.