SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States

1 code implementation • 7 Jun 2023 • Noga Mudrik, Gal Mishne, Adam S. Charles

Time series data across scientific domains are often collected under distinct states (e. g., tasks), wherein latent processes (e. g., biological factors) create complex inter- and intra-state variability.

Dictionary Learning Time Series

Multi-Lingual DALL-E Storytime

2 code implementations • 22 Dec 2022 • Noga Mudrik, Adam S. Charles

While DALL-E is a promising tool for many applications, its decreased performance when given input in a different language, limits its audience and deepens the gap between populations.

Human or Machine? Turing Tests for Vision and Language

no code implementations • 23 Nov 2022 • Mengmi Zhang, Giorgia Dellaferrera, Ankur Sikarwar, Marcelo Armendariz, Noga Mudrik, Prachi Agrawal, Spandan Madan, Andrei Barbu, Haochen Yang, Tanishq Kumar, Meghna Sadwani, Stella Dellaferrera, Michele Pizzochero, Hanspeter Pfister, Gabriel Kreiman

To address this question, we turn to the Turing test and systematically benchmark current AIs in their abilities to imitate humans.

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

1 code implementation • 7 Jun 2022 • Noga Mudrik, Yenho Chen, Eva Yezerets, Christopher J. Rozell, Adam S. Charles

Learning interpretable representations of neural dynamics at a population level is a crucial first step to understanding how observed neural activity relates to perception and behavior.

Dictionary Learning Time Series Analysis