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Supplemental Material: Low-shot Object Learning with Mutual Exclusivity Bias Anh Thai 1 Ahmad Humayun 2 Stefan Stojanov 1 Zixuan Huang
To render each view of the scenes, we first determine the camera position.
Dueling Over Dessert, Mastering the Art of Repeated Cake Cutting
We consider two versions: sequential, where Bob observes Alice's cut
ADGym: Design Choices for Deep Anomaly Detection
Many WSAD methods attribute their improvements to novel network architectures or loss functions, based on the authors' understanding of
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats
We present SCube, a novel method for reconstructing large-scale 3D scenes (geometry, appearance, and semantics) from a sparse set of posed images.
From Trainable Negative Depth to Edge Heterophily in Graphs Y uchen Y an
Upon increasing the depth, the over-smoothing issue arises: a GCN's
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification
Our study aims to promote a higher standard of empirical rigor in the field of graph machine learning, encouraging more accurate comparisons and evaluations of model capabilities.
Boosting Adversarial Transferability by Achieving Flat Local Maxima
Specifically, we randomly sample an example and adopt a first-order procedure to approximate the Hessian/vector product, which makes computing more efficient by interpolating two neighboring gradients.
