Recent Publications

• Generator Assisted Mixture of Experts For Feature Acquisition in Batch
  With Vedang Asgaonkar and Aditya Jain
  In AAAI, 2024
  [Paper | Code]

• Continuous Treatment Effect Estimation using Gradient Interpolation and Kernel Smoothing
  With N Lokesh, Akshay Iyer, and Sunita Sarawagi
  In AAAI, 2024
  [Paper | Code]

• Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search
  With Indradyumna Roy, Rishi Agarwal, Soumen Chakrabarti and Anirban Dasgupta
  In NeurIPS, 2023 (Spotlight)
  [Paper | Code]

• Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks
  With Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish V. Tendulkar and Rishabh Iyer
  In NeurIPS, 2023
  [Paper | Code]

• Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models
  With Parth Vipul Sangani, Arjun Shashank Kashettiwar, Pritish Chakraborty, Bhuvan Reddy Gangula, Durga S, Ganesh Ramakrishnan and Rishabh K Iyer.
  In ICML, 2023
  [Paper | Code]

• Differentiable Change-point Detection With Temporal Point Processes
  With Paramita Koley, Harshavardhan Alimi, Shrey Singla, Sourangshu Bhattacharya and Niloy Ganguly
  In AISTATS, 2023
  [Paper | Code]

• Learning and Maximizing Influence in Social Networks Under Capacity Constraints
  With Pritish Chakrabarti, Sayan Ranu and Ipsit Mantri
  In WSDM, 2023
  [Paper | Code]

• Learning Recourse on Instance Environment to Enhance Prediction Accuracy
  With Lokesh N, Guntakanti Sai Koushik and Sunita Sarawagi
  In NeurIPS, 2022
  [Paper | Code]

• Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection.
  With Soumen Chakrabarti
  In NeurIPS, 2022
  [Paper | Code]

• Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks
  With Indradyumna Roy and Soumen Chakrabarti
  In NeurIPS, 2022
  [Paper | Code]

• 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]

Older publications are here. For a complete list of publications, please see Google scholar or DBLP