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Jonathan Lorraine

lorraine2

https://www.jonlorraine.com/

AI & ML interests

machine learning, computer vision, generative AI

Recent Activity

authored a paper 9 days ago

JacNet: Learning Functions with Structured Jacobians

authored a paper 9 days ago

Variance Reduction for Expectations with Diffusion Teachers

authored a paper 9 days ago

NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation

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Posts 9

Post

1510

📽️ New NVIDIA paper: Motion Attribution for Video Generation 📽️

We propose MOTIVE, a method for taking query video clips and identifying which training data will improve or degrade performance after finetuning, enabling sophisticated data curation and beyond!

🔎 Project Page: https://research.nvidia.com/labs/sil/projects/MOTIVE/
📖 Full Paper: https://arxiv.org/abs/2601.08828

Check out more work from the NVIDIA Spatial Intelligence Lab here: https://research.nvidia.com/labs/sil/

This project was led by the great work of Xindi(Cindy) Wu, along with Despoina Paschalidou, Jun Gao, Antonio Torralba, Laura Leal-Taixé, Olga Russakovsky, and Sanja Fidler.

Post

545

🔊 New NVIDIA paper: Audio-SDS 🔊

We adapt Score Distillation Sampling (SDS), originally developed for text-to-3D generation, to audio diffusion models, allowing us to reuse large pretrained models for new text-guided parametric audio tasks such as source separation, physically informed impact synthesis, and more.

🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/Audio-SDS/
📖 Full Paper: https://arxiv.org/abs/2505.04621

Check out more from NVIDIA’s Spatial Intelligence Lab here: https://research.nvidia.com/labs/toronto-ai/

This project was led by the great work of Jessie Richter-Powell, along with Antonio Torralba.

Notably, we find a new and exciting use case for Stable Audio Open 🚀