Probabilistic Programming is a way of defining probabilistic models by overloading the operations in standard programming language to have probabilistic meanings. The goal is to specify probabilistic ...

We study machine learning formulations of inductive program synthesis; given input-output examples, we try to synthesize source code that maps inputs to corresponding outputs. Our aims are to develop ...

This project aims to create a deep learning model from scratch using PyTorch to be able to classify images of the American Sign Language (ASL) alphabet. The goal is for it to be able to accurately and ...

Translate - a PyTorch Language Library Translate is a library for machine translation written in PyTorch. It provides training for sequence-to-sequence models. Translate relies on fairseq, a general ...