Skip to content
Avatar
:octocat:
Learning Machine
:octocat:
Learning Machine

Achievements

Achievements

Highlights

  • Pro

Organizations

@lanl @UMBC-DREAM-Lab
Block or Report

Block or report MaksimEkin

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
MaksimEkin/README.md

I am a graduate Computer Science student and a SFS CyberCorps alumni at the University of Maryland, Baltimore County (UMBC). I received a BS in Computer Science Summa Cum Laude at UMBC. I work as a Research Assitant at Los Alamos National Laboratory (LANL) and at UMBC's DREAM Lab. My research interests lie at the intersection of the machine learning and cybersecurity disciplines, with a concentration in tensor decomposition.

Pinned

  1. CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent p…

    Python 4 2

  2. Python Distributed Non Negative Matrix Factorization with custom clustering

    Python 4 5

  3. Python Quantum Boolean Tensor Networks

    Python 3 1

  4. Python Distributed Non Negative Tensor Networks

    Python 5 4

  5. An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research art…

    HTML 75 48

  6. RFoT Public

    Random Forest of Tensors (RFoT) is a tensor decomposition based ensemble semi-supervised classifier.

    Python 1

703 contributions in the last year

May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Mon Wed Fri

Contribution activity

May 2022

Opened 1 pull request in 1 repository
lanl/pyCP_APR 1 merged
29 contributions in private repositories May 1 – May 21

Seeing something unexpected? Take a look at the GitHub profile guide.