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On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data
In disciplines such as chemistry, physics, and network science, graphs are a convenient and well-studied mathematical object to represent such interacting entities and their attributes.
TensorProgramsI
Please see https://arxiv.org/abs/1910.12478 for the full version of this paper.
PAC-Bayes Tree: weighted subtrees with guarantees
Neural Information Processing Systems http://nips.cc/
AQuantitativeGeometricApproachto Neural-NetworkSmoothness
The techniques for theโ2-perturbation do not easily transfer to theโ -case (Leino et al., 2021). One critical step is to measure the Lipschitz constant more precisely and efficiently.
AQuantitativeGeometricApproachto Neural-NetworkSmoothness
The techniques for theโ2-perturbation do not easily transfer to theโ -case (Leino et al., 2021). One critical step is to measure the Lipschitz constant more precisely and efficiently.
MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI T obit Klug 1, Kun Wang 1, Stefan Ruschke
In this paper, we propose MotionTTT a deep learning-based test-time-training (TTT) method for accurate motion estimation.
Neural Code Comprehension: A Learnable Representation of Code Semantics
Tal Ben-Nun, Alice Shoshana Jakobovits, Torsten Hoefler
Neural Information Processing Systems http://nips.cc/
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance Anonymous Author(s) Affiliation Address email
In what follows, we will focus on this regime and assume that d > n.
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance
Work done during an internship at Google Research 37th Conference on Neural Information Processing Systems (NeurIPS 2023).
Paraphrase Generation with Latent Bag of Words
Yao Fu, Yansong Feng, John P. Cunningham
Neural Information Processing Systems http://nips.cc/