Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
Vidéo
Temporal Difference Models: Deep Model-free RL for Model-based
Deep reinforcement learning (RL) has shown promising results for learning complex sequential decision-making behaviors in various environments. However, most successes have been exclusively in simulation, and results in real-world applications such as robotics are limited,…
Vidéo
Debiasing Evidence Approximations: On Importance-Weighted Autoencoders and Jackknife Variational Inference
The importance-weighted autoencoder (IWAE) approach of Burda et al. (2015) defines a sequence of increasingly tighter bounds on the marginal likelihood of latent variable models. Recently, Cremer et al. (2017) reinterpreted the IWAE bounds as…
Vidéo
Graph neural networks: Variations and applications
Many real-world tasks require understanding interactions between a set of entities. Examples include interacting atoms in chemical molecules, people in social networks and even syntactic interactions between tokens in program source code. Graph structured data…
Vidéo
NeuroSAT: Learning a SAT Solver from Single-Bit Supervision
I will present NeuroSAT, a message passing neural network that learns to solve SAT problems after only being trained as a classifier to predict satisfiability. Although it is not competitive with state-of-the-art SAT solvers, NeuroSAT…
Outil
Translator Human Parity Data
Human evaluation results and translation output for the Translator Human Parity Data release, as described in this blog post (opens in new tab). The Translator Human Parity Data release contains all human evaluation results and…
Projet
Question Answering (QA)
Question Answering (QA) aims to automatically answer natural language questions posed by human. In MSRA QA team, we are working on QA from two angles: Single-turn QA and Conversational QA. Single-turn QA takes a single question as input…
Projet
Natural Language Understanding (NLU)
Natural Language Understanding (NLU) aims to transform natural language texts (sentences or questions) into their formal meaning representations as machine executable programs. Currently, we are working on two NLU engines for the question answering task, based…
Vidéo
AirSim ZhangJiaJie Environment
Zhangjiaji National Park, China environment with AirSim plugin to fly simulated drones.
