Science is becoming increasingly computational. Experimental data must be logged, cleaned, checked and analysed. Data analysis often involves iterative trial and ...

If there’s one universal experience with AI-powered code development tools, it’s how they feel like magic until they don’t. One moment, you’re watching an AI agent slurp up your codebase and deliver a ...

We currently only officially support conda and pip packaging of spglib, with plans to expand to FedoraProject in the near future. We are looking for additional contributors to package on other linux ...

This resource organizes techniques for working with coding assistants by development stage (from requirements and planning through review and refactoring). The techniques draw from practitioners ...

Incremental development is a process whereby we build our program incrementally—often in small steps or by components. This is a structured, step-by-step approach to writing software. This approach ...

We present NeuralMag, a flexible and high-performance open-source Python library for micromagnetic simulations. NeuralMag leverages modern machine learning frameworks, such as PyTorch and JAX, to ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

This work will be of interest to the motor control community as well as neuroAI researchers interested in how bodies constrain neural circuit function. The authors present "MotorNet", a useful ...

Which learning goals must individual computational elements pursue to contribute to a network-level task solution? This local understanding is missing in both biological, but also artificial neural ...