5 citations · 9 across the 4 of their papers we have counts for
6 papers
A Follow-the-Leader Strategy using Hierarchical Deep Neural Networks with Grouped Convolutions
Jose Solomon, Francois Charette
The task of following-the-leader is implemented using a hierarchical Deep Neural Network (DNN) end-to-end driving model to match the direction and speed of a target pedestrian. The…
Hierarchical Sequence to Sequence Voice Conversion with Limited Data
Praveen Narayanan, Punarjay Chakravarty, Francois Charette +1
We present a voice conversion solution using recurrent sequence to sequence modeling for DNNs. Our solution takes advantage of recent advances in attention based modeling in the fi…
Hierarchical Multi-task Deep Neural Network Architecture for End-to-End Driving
Jose Solomon, Francois Charette
A novel hierarchical Deep Neural Network (DNN) model is presented to address the task of end-to-end driving. The model consists of a master classifier network which determines the…
Floer homology of fibrations I: Representing flow lines in Moore path spaces
Francois Charette
In their previous work, Barraud and Cornea enriched the Lagrangian Floer complex by adding cubical chains in the based loop space of the Lagrangian, and recovered the Leray-Serre s…
Key-Value Retrieval Networks for Task-Oriented Dialogue
Mihail Eric, Christopher D. Manning
Neural task-oriented dialogue systems often struggle to smoothly interface with a knowledge base. In this work, we seek to address this problem by proposing a new neural dialogue a…
A geometric refinement of a theorem of Chekanov
Francois Charette
We prove a conjecture of Barraud and Cornea in the monotone setting, refining a result of Chekanov on the Hofer distance between two Hamiltonian isotopic Lagrangian submanifolds.