Thi Ngan Dong, Graham Brogden, Gisa Gerold, Megha Khosla (2021), A multitask transfer learning framework for the prediction of virus-human protein-protein interactions, In BMC Bioinformatics Volume 22.

Iyiola E Olatunji, Wolfgang Nejdl, M. Khosla (2021), Membership Inference Attack on Graph Neural Networks, In IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications.

Jurek Leonhardt, A. Anand, M. Khosla (2020), Boilerplate removal using a neural sequence labeling model, In The Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020 p.226-229.

Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand (2020), Node Representation Learning for Directed Graphs, Ulf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, Céline Robardet (Eds.), In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings Volume 11906 p.395-411.

Megha Khosla, Avishek Anand (2019), A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs, In Algorithmica Volume 81 p.3707-3724.

Helge Holzmann, Avishek Anand, M. Khosla (2018), Delusive pagerank in incomplete graphs, In International Conference on Complex Networks and their Applications.

Jurek Leonhardt, Avishek Anand, Megha Khosla (2018), User Fairness in Recommender Systems, In Companion Proceedings of the The Web Conference 2018.

Nikolaos Fountoulakis, M. Khosla, Konstantinos Panagiotou (2015), The Multiple-Orientability Thresholds for Random Hypergraphs, In Combinatorics, Probability and Computing Volume 25.

M. Khosla (2013), Balls into Bins made Faster, In Proceedings of the Twenty-First Annual European Symposium on Algorithms.

Nikolaos Fountoulakis, M. Khosla, Konstantinos Panagiotou (2011), The Multiple-Orientability Thresholds for Random Hypergraphs, Dana Randall (Eds.), In Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete algorithms (SODA'11 Volume 25 p.1222-1236.