Data-driven Battery Model Identification in LPV Framework using Python
-
Updated
May 1, 2026 - Python
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)
Data repository of the work published in Huber et al. 2026.
Filtered Sequential Monte Carlo for time-varying model parameters analysis
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
Identify which LLM produced given answers — based on single-token behavioral fingerprints (Bruckner 2026, arXiv:2607.10252). 170 models, 10 tasks, 4 languages.
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.
Model identifiability pipeline using surrogate models trained on a latent space extracted by tensor decompositions.
To associate your repository with the model-identification topic, visit your repo's landing page and select "manage topics."