Supported projects

Supported projects

The EPICURE project supports a diverse range of initiatives, addressing support requests, e.g., from GPU and node optimization to code porting and performance benchmarking. Each project brings unique challenges and goals, and EPICURE provides the expertise and resources to help them succeed. On this page, you’ll find a selection of supported projects, showcasing EPICURE contribution.

Machine Learning of Exchange Energy Density and Integration with Python-based Electronic Structure Codes

Python framework with EPICURE optimizations boosts ML density functionals for better quantum chemistry transferability

Supported projects

Exploring additional computational resources for Latvian genome reference project

Scalable and Intelligent Traffic Modeling for Improved Urban Planning

Financial Virtual Assistant for Portfolio Management

Anthropogenic Stressors and Future Changes of the North West European Shelf ecosystem

HIDALGO 2 Wildfires deployment 2024

Enhancing EUBERT: Retraining the European Parliament’s LLM with Contemporary Parliamentary Data

Developing a Heart Language Foundation Model

Predictive Exploration of Correlation in Specific Interactions and Optimization Networks

Setting parameters in the Yambo new options for large systems

Removing cobalt from Hard Metals

BCPNNSim

Machine Learning of Exchange Energy Density and Integration with Python-based Electronic Structure Codes

Supported projects

Supported projects

Exploring additional computational resources for Latvian genome reference project

Scalable and Intelligent Traffic Modeling for Improved Urban Planning

Financial Virtual Assistant for Portfolio Management

Anthropogenic Stressors and Future Changes of the North West European Shelf ecosystem

HIDALGO 2 Wildfires deployment 2024

Enhancing EUBERT: Retraining the European Parliament’s LLM with Contemporary Parliamentary Data

Developing a Heart Language Foundation Model

Predictive Exploration of Correlation in Specific Interactions and Optimization Networks

Setting parameters in the Yambo new options for large systems

Removing cobalt from Hard Metals

BCPNNSim

Machine Learning of Exchange Energy Density and Integration with Python-based Electronic Structure Codes

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