Aditya Grover


Email: adityag at cs.stanford.edu

I am a second-year Ph.D student in the department of Computer Science at Stanford University advised by Stefano Ermon. I am broadly interested in the theory and applications of artificial intelligence. These days I am specifically looking at learning and inference in generative models.

Before joining Stanford, I finished my undergraduate studies majoring in Computer Science and Engineering at IIT Delhi. My undergraduate research was advised by Mausam and Parag Singla .

Conference Publications (Refereed and Archived)

  1. Variational Bayes on Monte Carlo Steroids
    Aditya Grover, Stefano Ermon
    Neural Information Processing Systems (NIPS), 2016. [PDF][Spotlight video]

  2. node2vec: Scalable Feature Learning for Networks
    Aditya Grover, Jure Leskovec
    Knowledge Discovery and Data Mining (KDD), 2016. [PDF][Code]
    Oral Plenary Presentation [acceptance rate: 70/784 (8.9%)]

  3. Contextual Symmetries in Probabilistic Graphical Models
    Ankit Anand, Aditya Grover, Mausam, Parag Singla
    International Joint Conference on Artificial Intelligence (IJCAI), 2016. [PDF]
    Also, won the Best Paper Award at the International Workshop on Statistical Relational AI (StarAI), 2016.

  4. A Deep Hybrid Model for Weather Forecasting
    Aditya Grover, Ashish Kapoor, Eric Horvitz
    Knowledge Discovery and Data Mining (KDD), 2015. [PDF] [Press Microsoft , Gizmodo]

  5. ASAP-UCT: Abstraction of State-Action Pairs in UCT
    Ankit Anand, Aditya Grover, Mausam, Parag Singla
    International Joint Conference on Artificial Intelligence (IJCAI), 2015. [PDF]

  6. A Novel Abstraction Framework for Online Planning (short)
    Ankit Anand, Aditya Grover, Mausam, Parag Singla
    International Conference on Autonomous Agents and Multi-agent Systems (AAMAS), 2015. [PDF]