Search Results for "python mini project"

Open Science is an open-source, local-first AI research workbench built for scientific discovery on macOS, Windows, and Linux. Researchers can describe a task in plain language and let an agent inspect files, execute Python or R, search the web, and call scientific data connectors. The system is model-agnostic, allowing users to connect supported providers, compatible gateways, or subscription-based backends. It produces reproducible reports, tables, figures, and other artifacts inside a unified project workspace. Users can inspect tool activity, approve sensitive actions, branch earlier conversations, and compare alternative research paths without losing prior work. ...

AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they...

JSONLab is a free and open-source JSON/UBJSON/MessagePack encoder and decoder written in the native MATLAB language. It can be used to convert a MATLAB data structure (array, struct, cell, struct array, cell array, and objects) into JSON/UBJSON/MessagePack formatted strings and files, or to parse a JSON/UBJSON/MessagePack file into MATLAB data structure. JSONLab supports nearly all versions of MATLAB and GNU Octave (a free MATLAB clone). The development of JSONLab is currently funded by the...

The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The...

The main goal of this project was developing phase-field simulations of lithium dendrite growth with FEniCS programmed in Python. The problem was based in the grand potential-based model of Zijian Hong and Venkatasubramanian Viswanathan (https://doi.org/10.1021/acsenergylett.8b01009) . Some simpler examples were developed before for a first approach with FEniCS: heat equation and combustion model.

StochKit is an extensible stochastic simulation framework developed in C++ that aims to make stochastic simulation accessible to practicing biologists and chemists, while remaining open to extension via new stochastic and multiscale algorithms. StochKit is part of the StochSS project [http://www.stochss.org/], and we are relying on continued funding for sustained development. Please consider registering to show your support. Register here: https://docs.google.com/forms/d/12tAH4f8CJ-3F-lK44Q9uQHFio_mGoK0oY829q5lD7i4/viewform GillesPy is a python interface for developing models and simulating them with StochKit. ...

...After observing the lack of ready-to-implement libraries for power system analisys, and that the existing ones focus on command line workflow, I decided myself to start a project to fill the gap. Since Power system simulations have started needing to be executed in parallel, the old C-like designs are outdated; modular design is now needed to launch many simulations at the same time based on a base circuit. fPotencia is programmed in C++, but my intention is to bring JAVA, C#, Python and perhaps MATLAB versions of it. ...