44 citations · 199 across the 22 of their papers we have counts for
4 papers · 1 filter
LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration
Ran Liu, Sahil Khose, Jingyun Xiao +4
Despite significant advances in deep learning, models often struggle to generalize well to new, unseen domains, especially when training data is limited. To address this challenge,…
Half-Hop: A graph upsampling approach for slowing down message passing
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor +6
Message passing neural networks have shown a lot of success on graph-structured data. However, there are many instances where message passing can lead to over-smoothing or fail whe…
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
Mehdi Azabou, Michael Mendelson, Nauman Ahad +4
Natural behavior consists of dynamics that are complex and unpredictable, especially when trying to predict many steps into the future. While some success has been found in buildin…
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction
Jorge Quesada, Lakshmi Sathidevi, Ran Liu +10
There are multiple scales of abstraction from which we can describe the same image, depending on whether we are focusing on fine-grained details or a more global attribute of the i…