Publications
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Sahil Manchanda*, Shubham Gupta*, Sayan Ranu and Srikanta Bedathur “Generative Modeling of Labeled Graphs under Data Scarcity” in LOG 2023. (*Joint authorship)
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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)
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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.
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Sahil Manchanda and Sayan Ranu “Lifelong Learning to solve Mixed Integer Programs”. in AAAI 2023.
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Sahil Manchanda, Sofia Michel, Darko Drakulic, Jean-Marc Andreoli “On the Generalization of Neural Combinatorial Optimization Heuristics” , ECML-PKDD 2022.
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Shubham Gupta, Sahil Manchanda, Srikanta Bedathur and Sayan Ranu, “TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs”, in AAAI 2022
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Jayant Jain, Vrittika Bagadia, Sahil Manchanda and Sayan Ranu, “NeuroMLR: Robust & Reliable Route Recommendation on Road Networks” , in NeurIPS, 2021.
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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.
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Sahil Manchanda and Ashish Anand “Representation Learning of Drug and Disease Terms for Drug Repositioning” - 3rd IEEE International Conference on Cybernetics, 2017.
Patent
- Trained Pattern Analyzer for Rollout Decisions” USPTO.
Inventors: Sahil Manchanda, Arun Rajkumar, Simarjot Kaur and Narayanan Unny.
Status : Granted 2022: USPTO