About Publications

    Publications

  • VarSCene: A Deep Generative Model for Realistic Scene Graph Synthesis
    With Tathagat Verma, Yatish Agarwal, Vishwa Vinay and Soumen Chakrabarti
    In ICML, 2022
    [Paper | Code]
  • Interpretable Neural Subgraph Matching for Graph Retrieval
    With Indradyumna Roy, Venkata Sai Velugoti and Soumen Chakrabarti
    In AAAI, 2022
    [Paper | Code]
  • Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences
    With Vinayak Gupta and Srikanta Bedathur
    In AAAI, 2022
    [Paper | Code]
  • Learning to Select Exogenous Events With Marked Temporal Point Process
    With Ping Zhang, Rishabh Iyer, Ashish Tendulkar and Gaurav Aggarwal
    In NeurIPS, 2021
    [Paper | Code]
  • Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time
    With Anshul Nasery, Soumyadeep Thakur, Vihari Piratla, and Sunita Sarawagi
    In NeurIPS, 2021
    [Paper | Code]
  • Differentiable Learning Under Triage
    With Nastaran Okati, and Manuel Gomez Rodriguez
    In NeurIPS, 2021
    [Paper | Code]
  • Counterfactual Explanations in Sequential Decision Making Under Uncertainty
    With Stratis Tsirtsis, and Manuel Gomez Rodriguez
    In NeurIPS, 2021
    [Paper | Code]

  • Training Data Subset Selection For Regression With Controlled Generalization Error
    With Durga Sivasubramanian, Rishabh Iyer and Ganesh Ramakrishnan
    In ICML, 2021
    [Paper | Code]
  • Grad-Match: A Gradient Matching based Data Subset Selection for Efficient Learning
    With Krishnateja Killamsetty, Durga S, Ganesh Ramakrishnan and Rishabh Iyer
    In ICML, 2021
    [Paper | Code]
  • Adversarial Permutation Guided Node Representations for Link Prediction
    With Indradyumna Roy and Soumen Chakrabarti
    In AAAI, 2021
    [Paper | Code]
  • Differentially Private Link Prediction With Protected Connections
    With Soumen Chakrabarti
    In AAAI, 2021
    [Paper | Code]
  • Classification Under Human Assistance
    With Nastaran Okati, Ali Zarezade and Manuel Gomez-Rodriguez
    In AAAI, 2021
    [Paper | Code]
  • Long Horizon Forecasting of Temporal Point Processes
    With Prathamesh Deshpande, Kamalesh Marathe and Sunita Sarawagi
    In WSDM, 2021
    [Paper]
  • On the Design of Consequential Ranking Algorithms
    With Behzad Tabibian, Vicenc Gomez and Manuel Gomez-Rodriguez
    In UAI, 2020
    [Paper]
  • Deep Neural Matching Models for Graph Retrieval
    With Utkarsh Gupta, Kunal Goyal and Soumen Chakrabarti
    In SIGIR, 2020
    [Paper | Code]
  • Designing Deep Generative Models for Molecular Graphs
    With Bidisha Samanta, Gourhari Jana, Pratim K. Chattaraj, Vicenc Gomez, Niloy Ganguly, and Manuel Gomez Rodriguez
    In JMLR, 2020
    Primilinary version published in AAAI, 2019 and in the Workshop of Theoretical Foundations and Applications of Deep Generative Models at ICML 2018
    [Paper | Code]
  • Regression Under Human Assistance
    With Paramita Koley, Niloy Ganguly and Manuel Gomez-Rodriguez
    In AAAI, 2020
    Presented in the Human Centric Machine Learning Workshop at NeurIPS, 2019
    [Paper]
  • Can a User Guess What Her Followers Want
    With Adish Singla, Utkarsh Upadhyay and Manuel Gomez-Rodriguez
    In WSDM, 2020
    Also presented in the Workshop of Behavioral EC at ACM EC, 2019
    [Paper|
  • Learning a Linear Influence Model Between Actors from Transient Opinion Dynamics
    With Sourangshu Bhattacharya, Parantapa Bhattacharya, Niloy Ganguly, and Soumen Chakrabarti
    In ACM Transactions on the Web, 2019
    [Paper | Code | Data]
  • Enhancing human learning via spaced repetition optimization
    With Behzad Tabibian, Utkarsh Upadhyay, Ali Zarezade, Bernhard Scholkopf and Manuel Gomez-Rodriguez
    In PNAS, 2019
    Also presented in the Machine Teaching Workshop at NeurIPS, 2017
    [Paper| Code]
  • Learning Network Traffic Dynamics Using Temporal Point Process
    With Avirup Saha, Niloy Ganguly, Sandip Chakraborty
    In IEEE Conference on Computer Communications (INFOCOM), 2019
    [Paper]
  • On the Complexity of Opinions and Online Discussions
    With Utkarsh Upadhyay, Ashish Pappu and Manuel Gomez Rodriguez
    In ACM Conference on Web Search and Data Mining (WSDM), 2019
    [Paper| Code]
  • Designing Deep Generative Models for Molecular Graphs
    With Bidisha Samanta, Gourhari Jana, Pratim K. Chattaraj, Niloy Ganguly, and Manuel Gomez Rodriguez
    In AAAI Conference on Artificial Intelligence (AAAI), 2019
    Also presented in the Workshop of Theoretical Foundations and Applications of Deep Generative Models at ICML 2018
    [Paper | Code]
  • Deep Reinforcement Learning of Marked Temporal Point Processes
    With Utkarsh Upadhyay and Manuel Gomez Rodriguez
    In the advances of Neural Information Processing Systems (NeurIPS), 2018
    [ Paper | Code]
  • CRPP: Competing Recurrent Point Process for Modeling Visibility Dynamics in Information Diffusion
    With Avirup Saha, Bidisha Samanta, Niloy Ganguly
    In ACM Conference of Knowledge and Information Management Systems (CIKM), 2018
    [Paper | Code |
  • Shaping Opinion Dynamics in Social Networks
    With Sourangshu Bhattacharya, and Niloy Ganguly
    In Proceedings of the International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), Pages: 1336-1344, 2018
    [Paper | Code | Data].
  • Steering Social Activity: A Stochastic Optimal Control Point of View
    With Ali Zarezade, Utkarsh Upadhyay, Hamid Rabiee, and Manuel Gomez Rodriguez
    In Journal of Machine Learning Research, vol:8(35), Pages: 1-35, 2018
    [Paper | Code]
  • Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks
    With Sourangshu Bhattacharya, and Niloy Ganguly
    In Proceedings of the World Wide Web Conference (WWW), Pages: 549-558, 2018,
    [Paper | Data]
  • Cheshire: An Online Algorithm for Activity Maximization in Social Networks
    With Ali Zarezade, Hamid Rabiee, and Manuel Gomez Rodriguez,
    Allerton Conference on Communication, Control, and Computing, 2017 (Invited Paper)
    [Paper]
  • SLANT+: A Nonlinear Model for Opinion Dynamics in Social Networks
    With Bhushan Kulkarni, Sumit Agarwal, Sourangshu Bhattacharya, and Niloy Ganguly
    In Proceedings of IEEE International Conference on Data Mining (ICDM), Pages: 931-936, 2017
    [Paper | Code | Data]
  • LMPP: A Large Margin Point Process Combining Reinforcement and Competition in Hashtag Popularity
    With Bidisha Samanta, Abhijnan Chakraborty, and Niloy Ganguly,
    In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Pages: 2679-2685, 2017
    [Paper | Code | Data].
  • STRM: A Sister Tweet Reinforcement Process for Modeling Hashtag Popularity
    With Bidisha Samanta and Niloy Ganguly
    In Proceedings of IEEE Conference on Computer Communications (INFOCOM), Pages: 1-9, 2017
    [Paper | Code | Data].
  • Learning and Forecasting Opinion Dynamics in Social Networks
    With Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, and Manuel Gomez Rodriguez
    In Advances in Neural Information Processing Systems (NIPS), Pages: 397-405, 2016
    [Paper | Code | Data| News-coverage| Spotlight]
  • Discriminative Link Prediction using Local, Community and Global Signals
    With Sourangshu Bhattacharya, Sourav Sarkar, Niloy Ganguly, and Soumen Chakrabarti
    In IEEE Transactions on Knowledge and Data Engineering, vol:28(8) Pages: 2057–2070, 2016
    [Paper]
  • Knowlywood: Mining Activity Knowledge From Hollywood Narratives,
    With Niket Tandon, Gerard De Melo and Gerhard Weikum,
    In Proceedings of the ACM International on Conference on Information and Knowledge Management (CIKM), Pages:223–232, 2015
    [Paper]
  • Lights, Camera, Action: Knowledge Extraction from Movie Scripts,
    With Niket Tandon, Gerard De Melo and Gerhard Weikum,
    Poster paper in the World Wide Web Conference (WWW), 2015,
    [Paper].
  • Learning a Linear Influence Model Between Actors from Transient Opinion Dynamics,
    With Sourangshu Bhattacharya, Parantapa Bhattacharya, Niloy Ganguly, and Soumen Chakrabarti,
    In Proceedings of the ACM International on Conference on Information and Knowledge Management (CIKM), Pages: 401-410, 2014,
    [Paper | Code | Data].
  • Discriminative Link Prediction using Local Links, Node Features and Community Structure,
    With Niloy Ganguly, and Soumen Chakrabarti,
    In Proceedings of IEEE International Conference on Data Mining (ICDM), Pages:1009-1014, 2013,
    [Paper].
  • Local Learning of Item Dissimilarity Using Content and Link Structure,
    With Maunendra Sankar Desarkar, Niloy Ganguly, and Pabitra Mitra,
    In Proceedings of ACM Conference on Recommender Systems (RecSys), Pages: 221–224, 2012, [Paper].