Alexandre Marcireau

Discover how Vector Symbolic Algebras enable Bayesian optimization that matches state-of-the-art robotics results without cubic scaling in sample count.

We are pivoting the Open Neuromorphic Research (ONR) program from a formal peer-review pipeline to a dynamic, community-highlighted research feed featuring Gold and Silver openness tiers.

We are thrilled to announce the development of 'Zero to Silicon', a summer school series designed to take you from zero hardware background to simulating a digital neuromorphic chip. We need volunteers to make it happen!

Meet the new leadership team elected with a mandate to evolve ONM's structure and drive key initiatives in education and open science.

Implementing ROSBag format support in Faery demonstrates how compiling Rust modules into a Python API ensures high-performance event data decoding.

Nine neuromorphic tool maintainers navigate open-source funding, standardize edge deployments, and successfully balance commercial scale with biological realism.

Discover the architectural decisions behind Faery v0.3.0, including its new MP4 conversion pipeline, dynamic CLI reflection, and Rust-based build challenges.

See how the Faery API handles event-stream regularization and custom CLI parsers to efficiently render uncalibrated neuromorphic event data into MP4 video.

The Faery library's CLI design uses UNIX-style piping to simplify event camera data conversions and complex, real-time filtering pipelines.

Faery's stream-based API and the Neuromorphic Intermediate Representation (NIR) enable deploying models to Innatera's mixed-signal edge chips.

Explore how to use GitHub Actions and cibuildwheel to automate cross-platform compilation and deployment of the Rust-backed Faery event processing library.

Discover methods to efficiently encode and store event-based data from high-resolution event cameras, striking a balance between file size and fast retrieval for spiking neural network training.