LightOn

RITA is a family of autoregressive protein models, developed by LightOn in collaboration with the OATML group at Oxford and the Debora Marks Lab at Harvard.

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Study on the applicability of Direct Feedback Alignment to neural view synthesis, recommender systems, geometric learning, and natural language processing.

lightonai

Double Descent Curve with Optical Random Features

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Inference code in Pytorch for GPT-like models, such as PAGnol, a family of models with up to 1.5B parameters, trained on datasets in French.

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Python library for running large-scale computations on LightOn's OPUs

lightonai

Implementation of NEWMA: a new method for scalable model-free online change-point detection

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Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)

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ML benchmarks performance featuring LightOn's Optical Processing Unit (OPU) vs CPU and GPU.

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Code for our paper on best practices to train neural networks with direct feedback alignment (DFA).

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Code to perform Model-Free Episodic Control using Aurora OPUs

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