416 citations · 861 across the 11 of their papers we have counts for
14 papers
Implementation of AI/Deep Learning Disruption Predictor into a Plasma Control System
William Tang, Ge Dong, Jayson Barr +17
This paper reports on advances to the state-of-the-art deep-learning disruption prediction models based on the Fusion Recurrent Neural Network (FRNN) originally introduced a 2019 N…
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu, Daya Guo, Shuo Ren +19
Benchmark datasets have a significant impact on accelerating research in programming language tasks. In this paper, we introduce CodeXGLUE, a benchmark dataset to foster machine le…
PyMT5: multi-mode translation of natural language and Python code with transformers
Colin B. Clement, Dawn Drain, Jonathan Timcheck +2
Simultaneously modeling source code and natural language has many exciting applications in automated software development and understanding. Pursuant to achieving such technology,…
Generating Accurate Assert Statements for Unit Test Cases using Pretrained Transformers
Michele Tufano, Dawn Drain, Alexey Svyatkovskiy +1
Unit testing represents the foundational basis of the software testing pyramid, beneath integration and end-to-end testing. Automated software testing researchers have proposed a v…
GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu +15
Pre-trained models for programming language have achieved dramatic empirical improvements on a variety of code-related tasks such as code search, code completion, code summarizatio…
Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science
Ge Dong, Kyle Gerard Felker, Alexey Svyatkovskiy +2
We have trained a fully convolutional spatio-temporal model for fast and accurate representation learning in the challenging exemplar application area of fusion energy plasma scien…
IntelliCode Compose: Code Generation Using Transformer
Alexey Svyatkovskiy, Shao Kun Deng, Shengyu Fu +1
In software development through integrated development environments (IDEs), code completion is one of the most widely used features. Nevertheless, majority of integrated developmen…
Fast and Memory-Efficient Neural Code Completion
Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi +3
Code completion is one of the most widely used features of modern integrated development environments (IDEs). While deep learning has made significant progress in the statistical p…
Training Distributed Deep Recurrent Neural Networks with Mixed Precision on GPU Clusters
Alexey Svyatkovskiy, Julian Kates-Harbeck, William Tang
In this paper, we evaluate training of deep recurrent neural networks with half-precision floats. We implement a distributed, data-parallel, synchronous training algorithm by integ…
Pythia: AI-assisted Code Completion System
Alexey Svyatkovskiy, Ying Zhao, Shengyu Fu +1
In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia. It generates ranked lists of method and API recommendations which can be used b…
Using Big Data Technologies for HEP Analysis
Matteo Cremonesi, Claudio Bellini, Bianny Bian +17
The HEP community is approaching an era were the excellent performances of the particle accelerators in delivering collision at high rate will force the experiments to record a lar…
CMS Analysis and Data Reduction with Apache Spark
Oliver Gutsche, Luca Canali, Illia Cremer +12
Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software an…
Principal-component analysis of two-particle azimuthal correlations in PbPb and pPb collisions at CMS
CMS Collaboration
For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis…
Big Data in HEP: A comprehensive use case study
Oliver Gutsche, Matteo Cremonesi, Peter Elmer +7
Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and compu…