43 citations · 69 across the 8 of their papers we have counts for
9 papers
Towards a Linear-Algebraic Hypervisor
Breandan Considine
Many techniques in program synthesis, superoptimization, and array programming require parallel rollouts of general-purpose programs. GPUs, while capable targets for domain-specifi…
A Word Sampler for Well-Typed Functions
Breandan Considine
We describe an exact sampler for a simply-typed, first-order functional programming language. Given an acyclic finite automaton, , it samples a random function uni…
Syntax Repair as Language Intersection
Breandan Considine
Syntax repair can be viewed as a question about finite languages: given an invalid string and a grammar, which nearby strings are syntactically valid? We formalize bounded syntax r…
A Tree Sampler for Bounded Context-Free Languages
Breandan Considine
In the following paper, we present a simple method for sampling trees with or without replacement from BCFLs. A BCFL is a context-free language (CFL) corresponding to an incomplete…
Idiolect: A Reconfigurable Voice Coding Assistant
Breandan Considine, Nicholas Albion, Xujie Si
This paper presents Idiolect, an open source (https://github.com/OpenASR/idiolect) IDE plugin for voice coding and a novel approach to building bots that allows for users to define…
gradSim: Differentiable simulation for system identification and visuomotor control
Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo +11
We consider the problem of estimating an object's physical properties such as mass, friction, and elasticity directly from video sequences. Such a system identification problem is…
The AI Driving Olympics at NeurIPS 2018
Julian Zilly, Jacopo Tani, Breandan Considine +14
Despite recent breakthroughs, the ability of deep learning and reinforcement learning to outperform traditional approaches to control physically embodied robotic agents remains lar…
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Isabela Albuquerque, João Monteiro, Thang Doan +3
Recent literature has demonstrated promising results for training Generative Adversarial Networks by employing a set of discriminators, in contrast to the traditional game involvin…
Deep Pepper: Expert Iteration based Chess agent in the Reinforcement Learning Setting
Sai Krishna G. V., Kyle Goyette, Ahmad Chamseddine +1
An almost-perfect chess playing agent has been a long standing challenge in the field of Artificial Intelligence. Some of the recent advances demonstrate we are approaching that go…