Brian C. Van Essen
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View article: AI@DOE Interim Executive Report
AI@DOE Interim Executive Report Open
Interim executive report for DOE’s Office of Science, NNSA, and Applied Energy Offices, in collaboration with the Artificial Intelligence and Technology Office, DOE AI roundtable workshops (December 2021 through February 2022) (“AI@DOE”). …
View article: Machine learning–driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins
Machine learning–driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins Open
Significance Here we present an unprecedented multiscale simulation platform that enables modeling, hypothesis generation, and discovery across biologically relevant length and time scales to predict mechanisms that can be tested experimen…
View article: Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications Open
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural ne…
View article: Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications Open
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural ne…
View article: A State-of-the-Art Survey on Deep Learning Theory and Architectures
A State-of-the-Art Survey on Deep Learning Theory and Architectures Open
In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some n…
View article: Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency Open
Gene expression profiles have been widely used to characterize patterns of cellular responses to diseases. As data becomes available, scalable learning toolkits become essential to processing large datasets using deep learning models to mo…
View article: Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor
Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor Open
Due to the distributed and asynchronous nature of neural computation through low-energy spikes, brain-inspired hardware systems offer high energy efficiency and massive parallelism. One such platform is the IBM TrueNorth neurosynaptic syst…
View article: Effective Quantization Approaches for Recurrent Neural Networks
Effective Quantization Approaches for Recurrent Neural Networks Open
Deep learning, and in particular Recurrent Neural Networks (RNN) have shown superior accuracy in a large variety of tasks including machine translation, language understanding, and movie frame generation. However, these deep learning appro…
View article: The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches
The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches Open
Deep learning has demonstrated tremendous success in variety of application domains in the past few years. This new field of machine learning has been growing rapidly and applied in most of the application domains with some new modalities …
View article: Argo NodeOS: Toward Unified Resource Management for Exascale
Argo NodeOS: Toward Unified Resource Management for Exascale Open
Exascale systems are expected to feature hundreds of thousands of compute nodes with hundreds of hardware threads and complex memory hierarchies with a mix of on-package and persistent memory modules. In this context, the Argo project is d…