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Publications

  1. Sahil Manchanda*, Shubham Gupta*, Sayan Ranu and Srikanta Bedathur “Generative Modeling of Labeled Graphs under Data Scarcity” in LOG 2023. (*Joint authorship)

  2. Shubham Gupta*, Sahil Manchanda*, Sayan Ranu and Srikanta Bedathur “GRAFENNE: Continual learning on Graphs with Heterogeneous and Dynamic Feature Sets” in ICML 2023. (*Joint authorship)

  3. Vaibhav Bihani, Sahil Manchanda, Srikant Sastry, Sayan Ranu and Anoop Krishnan “StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes” ICML 2023.

  4. Sahil Manchanda and Sayan Ranu “Lifelong Learning to solve Mixed Integer Programs”. in AAAI 2023.

  5. Sahil Manchanda, Sofia Michel, Darko Drakulic, Jean-Marc Andreoli “On the Generalization of Neural Combinatorial Optimization Heuristics” , ECML-PKDD 2022.

  6. Shubham Gupta, Sahil Manchanda, Srikanta Bedathur and Sayan Ranu, “TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs”, in AAAI 2022

  7. Jayant Jain, Vrittika Bagadia, Sahil Manchanda and Sayan Ranu, “NeuroMLR: Robust & Reliable Route Recommendation on Road Networks” , in NeurIPS, 2021.

  8. Sahil Manchanda, Akash Mittal, Anuj Dhawan, Sourav Medya, Sayan Ranu, and Ambuj Singh “GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs”, in NeurIPS, 2020.

  9. Sahil Manchanda and Ashish Anand “Representation Learning of Drug and Disease Terms for Drug Repositioning” - 3rd IEEE International Conference on Cybernetics, 2017.

Patent

  1. Trained Pattern Analyzer for Rollout Decisions” USPTO.
    Inventors: Sahil Manchanda, Arun Rajkumar, Simarjot Kaur and Narayanan Unny.
    Status : Granted 2022: USPTO