Welcome to Lucas's Document Repository

Below are works of mine. Also take a look at a compilation of readings aligned with my interests.

Library Learning for Neurally-Guided Bayesian Program Induction [link]
2018, NIPS Spotlight. Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer, Armando Solar-Lezama, Joshua B. Tenenbaum
On the Representation and Learning of Concepts: Programs, Types, and Bayes [paper][bibtex]
2018, Thesis for Master of Engineering
Natively run OCaml from Rust [link]
2018, Blog Post with Mathias Sablé-Meyer
Concept Representation in a Type System [workshop][slides]
2018, Talk at Learning as Program Induction Workshop, CogSci Conference
Markov Chain Convergence [paper]
2017, Algorithmic Aspects of Machine Learning (18.408) Final Project
Automatic Least-Effort Contextual Learning [paper][code]
2017, SuperUROP Research Project
Free Software (as in Freedom) [7:52] [mp4][webm]
2017, Short Documentary (CMS.335) Final Project
Learning Expressive Contextual Grammars in Lambda Calculus [paper]
2016, Computation and Linguistic Theory (24.S95) Final Project
Group Sparsity with Probabilistic Feature Clustering [paper][poster]
2016, Statistical Learning Theory (9.520) Final Project
Theory Learning as Informed Stochastic Program Synthesis [paper]
2015, Computational Cognitive Science (9.660) Final Project
Distributed Ambient Environment Sensing [paper]
2015, Computer Systems Engineering (6.033) Design Project Report

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