603 citations · 1.1k across the 11 of their papers we have counts for
15 papers
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian +3
Generative Flow Networks (GFlowNets), a class of generative models over discrete and structured sample spaces, have been previously applied to the problem of inferring the marginal…
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes
Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian +2
Bayesian causal structure learning aims to learn a posterior distribution over directed acyclic graphs (DAGs), and the mechanisms that define the relationship between parent and ch…
A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions
Francois St-Hilaire, Dung Do Vu, Antoine Frau +28
Despite artificial intelligence (AI) having transformed major aspects of our society, less than a fraction of its potential has been explored, let alone deployed, for education. AI…
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch +5
Data efficiency is a key challenge for deep reinforcement learning. We address this problem by using unlabeled data to pretrain an encoder which is then finetuned on a small amount…
Comparative Study of Learning Outcomes for Online Learning Platforms
Francois St-Hilaire, Nathan Burns, Robert Belfer +16
Personalization and active learning are key aspects to successful learning. These aspects are important to address in intelligent educational applications, as they help systems to…
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar +6
We present Korbit, a large-scale, open-domain, mixed-interface, dialogue-based intelligent tutoring system (ITS). Korbit uses machine learning, natural language processing and rein…