Oceania
Ode to an ODE Krzysztof Choromanski Robotics at Google NY Jared Quincy Davis DeepMind & Stanford University V alerii Likhosherstov
This led to successful applications of Neural ODEs in machine learning.
Supplementto" TheOut-of-DistributionProblemin ExplainabilityandSearchMethodsforFeatureImportance Explanations " AMethodImplementationandHyperparameterTuningDetails
Do feature attribution methods correctly attribute features?
TheOut-of-DistributionProbleminExplainability andSearchMethodsforFeatureImportance Explanations
To resolvethis issue, we propose asimple alteration to the model training process, which results in more socially aligned explanations and metrics.
Equivariant Networksfor Crystal Structures
Open Catalyst 2020 (OC20) Datasetand Community Challenges // ACSCatalysis.
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models George Stein Jesse C. Cresswell Rasa Hosseinzadeh Yi Sui Brendan Leigh Ross
We address these flaws through a study of alternative self-supervised feature extractors, find that the semantic information encoded by individual networks strongly depends on their training procedure, and show that DINOv2-ViT -L/14 allows for much richer evaluation of generative models.
