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38 papers · 1 filter
NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework
Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian +7
We present SimNet, an AI-driven multi-physics simulation framework, to accelerate simulations across a wide range of disciplines in science and engineering. Compared to traditional…
Removing Class Imbalance using Polarity-GAN: An Uncertainty Sampling Approach
Kumari Deepshikha, Anugunj Naman
Class imbalance is a challenging issue in practical classification problems for deep learning models as well as for traditional models. Traditionally successful countermeasures suc…
Online Adaptation for Consistent Mesh Reconstruction in the Wild
Xueting Li, Sifei Liu, Shalini De Mello +4
This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild. Without requiring annotations of 3D mesh, 2D…
Personalized Federated Learning with First Order Model Optimization
Michael Zhang, Karan Sapra, Sanja Fidler +2
While federated learning traditionally aims to train a single global model across decentralized local datasets, one model may not always be ideal for all participating clients. Her…
A study of traits that affect learnability in GANs
Niladri Shekhar Dutt, Sunil Patel
Generative Adversarial Networks GANs are algorithmic architectures that use two neural networks, pitting one against the opposite so as to come up with new, synthetic instances of…
Rapid Exploration of Optimization Strategies on Advanced Architectures using TestSNAP and LAMMPS
Rahulkumar Gayatri, Stan Moore, Evan Weinberg +5
The exascale race is at an end with the announcement of the Aurora and Frontier machines. This next generation of supercomputers utilize diverse hardware architectures to achieve t…