8 citations · 9 across the 3 of their papers we have counts for
3 papers
Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow
Varun Shankar, Gavin D. Portwood, Arvind T. Mohan +6
In fluid physics, data-driven models to enhance or accelerate solution methods are becoming increasingly popular for many application domains, such as alternatives to turbulence cl…
Parallelized Training of Restricted Boltzmann Machines using Markov-Chain Monte Carlo Methods
Pei Yang, Srinivas Varadharajan, Lucas A. Wilson +4
Restricted Boltzmann Machine (RBM) is a generative stochastic neural network that can be applied to collaborative filtering technique used by recommendation systems. Prediction acc…
Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models
Derya Cavdar, Valeriu Codreanu, Can Karakus +11
Neural machine translation - using neural networks to translate human language - is an area of active research exploring new neuron types and network topologies with the goal of dr…