AI News, Aditya Grover artificial intelligence

Our Team

Machine Intelligence www.ceadar.ie The Centre which is funded by EI and the IDA has over 80 member companies across a wide span of industries.

The role involved prospecting for FinTech technology and investment opportunities across Europe, understanding developments in the European innovation ecosystem, and directing technology trials.

He has been awarded several international prizes including the Scientific American top 50 technologies that demonstrate outstanding leadership, Grand Award and Overall Winner for Innovation, Popular Science (USA), Horizon Award “10 Cool Cutting Edge Technologies”, Computer World (USA).

Publications (Google Scholar Profile)

Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

(* means Equal Contribution) Separate to Adapt: Open Set Domain Adaptation via Progressive Separation Hong Liu*, Zhangjie Cao*, Mingsheng Long, Jianmin Wang, Qiang Yang.

Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

(* means Equal Contribution) Universal Domain Adaptation Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I.

Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

AAAI Conference on Artificial Intelligence (AAAI), 2019.

(* means Equal Contribution) Transfer Adversarial Hashing for Hamming Space Retrieval Zhangjie Cao, Mingsheng Long, Chao Huang, Jianmin Wang.

AlignFlow: Auto cycle-consistent domain translations via normalizing flows Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon.

Aditya Grover, "node2vec: Scalable Feature Learning for Networks"

Aditya Grover, Jure Leskovec "node2vec: Scalable Feature Learning for Networks" Stanford University CompSust-2016 4th International Conference on ...

A Deep Hybrid Model for Weather Forecasting

Authors: Aditya Grover, Ashish Kapoor, Eric Horvitz Abstract: Weather forecasting is a canonical predictive challenge that has depended primarily on ...

Intuitive Teleoperation via VAEs

End of course project for Stanford's CS236: Deep Generative Models. Thanks to the course staff, Stefano Ermon, and Aditya Grover.

node2vec: Scalable Feature Learning for Networks

Author: Aditya Grover, Department of Computer Science, Stanford University Abstract: Prediction tasks over nodes and edges in networks require careful effort in ...

MIT 6.S191: Deep Generative Modeling

MIT Introduction to Deep Learning 6.S191: Lecture 4 *New 2019 Edition* Deep Generative Modeling Lecturer: Alexander Amini January 2019 For all lectures, ...

DeepWalk: Turning Graphs Into Features via Network Embeddings

Dr. Steven Skiena, Stony Brook University Michael Hunger, Neo4j Random walk algorithms help better model real-world scenarios, and when applied to graphs, ...

Geometric Deep Learning on Graphs and Manifolds - #NIPS2017

The purpose of the proposed tutorial is to introduce the emerging field of geometric deep learning on graphs and manifolds, overview existing solutions and ...

Variational Bayes on Monte Carlo Steroids

Spotlight video for the paper "Variational Bayes on Monte Carlo Steroids" by Aditya Grover and Stefano Ermon from Stanford University presented at NIPS 2016.

Vijay Gabale – Taking Fashion and Lifestyle Commerce Towards SKUs Using Deep Image and Text Parsing

In this talk, I will describe challenges, insights, innovations and experiences in building a large-scale deep learning system to prepare SKUs (Stock Keeping ...

A Deep Hybrid Model for Weather Forecasting (KDD 2015 Presentation)

A Deep Hybrid Model for Weather Forecasting KDD 2015 Presentation Aditya Grover Ashish Kapoor Eric Horvitz Weather forecasting is a canonical predictive ...