School of Mathematics, Computer Science & Engineering
  1. About the School
  2. Research
  3. Engineering & Mathematics scholarships & funding
  4. Computer Science scholarships and funding
  5. Placements and internships
  6. Our London location
  1. Resources
School of Mathematics, Computer Science & Engineering

Resources

The Neural-Symbolic system CILP++, developed by Manoel Franca, is available at sourceforge.

Code on RBMs, Sparse RBMs, and Classification RBMs, developed by Son Tran, is available at github.

Python code for a generalisation of the the Discriminative Restricted Boltzmann Machine by Srikanth Cherla, based on the work presented in this paper is available on this GitLab repository.

The centre also hosts a High Performance Computing Server with the following specs:

Processors: 20 Cores (2 x 10 Core Xenon Processors) Model: Intel XEON E5-2680v2, 2.8GHz, 25M Cache
Ram: 128BG
Disk space: 12TB (6 x 2TB disks).
Operating system: Ubuntu
Graphics Cards: 2 Nvidia Quadro K4000 cards
Software: Hadoop, Spark etc.
Availability: The server will be in use 24 * 7
Backup solution: Raid 5 or 6