Rajan, Vaibhav

11 publications

ICLR 2025 GANDALF: Generative AttentioN Based Data Augmentation and Predictive modeLing Framework for Personalized Cancer Treatment Aishwarya Jayagopal, Yanrong Zhang, Robert John Walsh, Tuan Zea Tan, Anand D Jeyasekharan, Vaibhav Rajan

ICLR 2024 Encoding Unitig-Level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, Vaibhav Rajan

ICML 2024 WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer Kumar Shubham, Aishwarya Jayagopal, Syed Mohammed Danish, Prathosh Ap, Vaibhav Rajan

NeurIPS 2022 Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction Hansheng Xue, Vaibhav Rajan, Yu Lin

AAAI 2022 RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning Hansheng Xue, Vijini Mallawaarachchi, Yujia Zhang, Vaibhav Rajan, Yu Lin

ICML 2020 Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization Debabrata Mahapatra, Vaibhav Rajan

MLJ 2019 Deep Collective Matrix Factorization for Augmented Multi-View Learning Ragunathan Mariappan, Vaibhav Rajan

AAAI 2019 Inferring Concept Prerequisite Relations from Online Educational Resources Sudeshna Roy, Meghana Madhyastha, Sheril Lawrence, Vaibhav Rajan

AAAI 2017 ICU Mortality Prediction: A Classification Algorithm for Imbalanced Datasets Sakyajit Bhattacharya, Vaibhav Rajan, Harsh Shrivastava

MLJ 2017 Vine Copulas for Mixed Data : Multi-View Clustering for Mixed Data Beyond Meta-Gaussian Dependencies Lavanya Sita Tekumalla, Vaibhav Rajan, Chiranjib Bhattacharyya

IJCAI 2016 Dependency Clustering of Mixed Data with Gaussian Mixture Copulas Vaibhav Rajan, Sakyajit Bhattacharya