no code implementations • 24 Jan 2024 • Josue Casco-Rodriguez, Caleb Kemere, Richard G. Baraniuk
Kalman filters provide a straightforward and interpretable means to estimate hidden or latent variables, and have found numerous applications in control, robotics, signal processing, and machine learning.
no code implementations • 4 Jul 2023 • Sina AlEMohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
Seismic advances in generative AI algorithms for imagery, text, and other data types has led to the temptation to use synthetic data to train next-generation models.
no code implementations • 19 Mar 2023 • Kai Malcolm, Josue Casco-Rodriguez
Biological neural networks continue to inspire breakthroughs in neural network performance.
1 code implementation • 12 Jan 2023 • Josue Casco-Rodriguez
Deep learning has recently empowered and democratized generative modeling of images and text, with additional concurrent works exploring the possibility of generating more complex forms of data, such as audio.
no code implementations • 21 Oct 2022 • Lorenzo Luzi, Paul M Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard G. Baraniuk
As implied by its name, Boomerang local sampling involves adding noise to an input image, moving it closer to the latent space, and then mapping it back to the image manifold through a partial reverse diffusion process.