lava-nc/lava-dl
Deep Learning library for Lava
This project helps researchers and engineers develop and deploy Deep Event-Based Networks, which are specialized neural networks that process information from event-based sensors like neuromorphic cameras. It takes in raw event data or pre-processed event streams and outputs a trained network model that can be used for tasks such as image classification, object detection, or regression. The primary users are neuromorphic computing researchers, AI/ML engineers working with event-based data, and specialists in real-time embedded AI.
174 stars. Available on PyPI.
Use this if you are developing AI applications for event-based sensors and need tools to efficiently train and deploy deep learning models that leverage the unique characteristics of event data.
Not ideal if your primary focus is on traditional frame-based deep learning (e.g., standard image or video processing) without an emphasis on event-based or neuromorphic computing.
Stars
174
Forks
78
Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Dependencies
12
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lava-nc/lava-dl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
pymc-devs/pytensor
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions...
arogozhnikov/einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
tensorly/tensorly
TensorLy: Tensor Learning in Python.
tensorpack/tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
tensorlayer/TensorLayerX
TensorLayerX: A Unified Deep Learning and Reinforcement Learning Framework for All Hardwares,...