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Max Planck Institute of Colloids and Interfaces
- Berlin
- https://orcid.org/my-orcid?orcid=0000-0002-7884-5017
Stars
Materials for short, half-day workshops
Official code repository for GATK versions 4 and up
Open standard for machine learning interoperability
An improved temporal data pipeline with foundational model for battery State of Health (SOH) prediction (R²->0.99) using advanced time series decomposition (D3R, CEEMDAN) and transformer-based meth…
Complete implementation with 3 methods, sensitivity analysis, and comprehensive visualizations. Reference: doi.org/10.1002/advs.202407641"
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c…
This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020. For HD commercial model, please try out Sync Labs
All benchmarks, examples and applications cases to be run by Kratos. Note that unit tests are in Kratos repository and NOT here
Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
Forecasting crude oil price using CEEMNDAN CNN LSTM
Machine Learning Predicts Renal Cell Carcinoma Status from Urine Using Multiplatform Metabolomics
CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.
🍻 An open-source dataset of breweries, cideries, brewpubs, and bottleshops.
Official Edison Lab toolboxes and scripts for analyzing metabolomics data.
Fermentation monitoring and management software
OpenFOAM examples for data-driven ML and ROM
The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs and CPUs via OpenCL. Free for non-commercial use.
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations