Massive Computational Experiments enabled Data ScienceAn integrated framework to introduce AI as an automation engine for conducting massive computational experiments that are needed by data science.
Combinatorial inference, structure learning, nonparametric methods
Massive Computational Experiments enabled Artificial IntelligenceAn AI-enabled framework for massive data acquisition and inform optimal decisions using massive computational experiments.
Deep learning, statistical machine learning.
Massive Computational Experiments enabled RoboticsBuild programmable machines that carry out physical processes and are controllable by an artificial intelligence system.
Deep reinforcement learning, natural language understanding, computer vision.
Data Science
Project: Combinatorial Inference.
Infering the topological and geometrical properties of high dimensional probabilistic graphical models.
Artificial Intelligence
Project: Simulational Inference
Learning the deep representation of data using large-scale computational experiments.
Robotics
Project: Decision making under uncertainty.
A massive scale simulation based approach to develop and deploy intelligent robots.
Ace: An AI-enabled Framework for Massive Computational Experiments
Keywords: Programing language, database, distributed computation, compliers, human-computer interaction.
Building an AI-centric operating system for managing massive computational experiments, with applications to science, engineering, and business.
Highlights
We currently highlight:
Combinatorial Inference for Graphical Models
April 6th, 2019 | Paper
Matey Neykov, Junewei Lu and Han Liu.