Blog

Research Compute Infrastructure

compute

infrastructure

Our research lab needed a more scalable approach to sharing computing resources among researchers. To address this, we built a scalable computing infrastructure on Kubernetes. Researchers can request resources from the pool and use a familiar workflow with Jupyter notebooks. Resources are returned to the pool once a task is complete or idle for too long.

Generative Adversarial Networks

pytorch

GAN

Generative Adversarial Networks (GANs) represent an innovative class of unsupervised neural networks that have revolutionized the field of artificial intelligence. Eager to learn how they work, I’ve implemented foundational “vanilla” GAN and its more complex counterpart, the Deep Convolutional GAN (DCGAN), from scratch. I’ve put them on a test run on MNIST Digits and Fashion toy datasets.

Neural Style Transfer

pytorch

NST

Neural Style Transfer (NST) was a breakthrough deep learning approach that can transfer artistic style from one image to another. Eager to learn how it works, I’ve implemented the original approach from scratch.