| 2016 | COMAD | Supervised Learning in Matrix Completion Framework for Recommender System Design. | Anupriya Gogna, Angshul Majumdar |
| 2016 | DCC | Fast Acquisition for Quantitative MRI Maps: Sparse Recovery from Non-Linear Measurements. | Anupriya Gogna, Angshul Majumdar |
| 2016 | ICONIP | Semi Supervised Autoencoder. | Anupriya Gogna, Angshul Majumdar |
| 2016 | ICONIP | Kernel L1-Minimization: Application to Kernel Sparse Representation Based Classification. | Anupriya Gogna, Angshul Majumdar |
| 2016 | ICONIP | Nuclear Norm Regularized Randomized Neural Network. | Anupriya Gogna, Angshul Majumdar |
| 2016 | ICONIP | Stacked Robust Autoencoder for Classification. | Janki Mehta, Kavya Gupta, Anupriya Gogna, Angshul Majumdar, Saket Anand |
| 2016 | ICONIP | Deep Dictionary Learning vs Deep Belief Network vs Stacked Autoencoder: An Empirical Analysis. | Vanika Singhal, Anupriya Gogna, Angshul Majumdar |
| 2015 | ICASSP | Design of signal-matched critically sampled FIR rational filterbank. | Anupriya Gogna, Sri Harsha Gade, Anubha Gupta |
| 2014 | COMAD | Distributed Elastic Net Regularized Blind Compressive Sensing for Recommender System Design. | Anupriya Gogna, Angshul Majumdar |
| 2014 | ICIP | Split Bregman algorithms for sparse / joint-sparse and low-rank signal recovery: Application in compressive hyperspectral imaging. | Anupriya Gogna, Ankita Shukla, Hemant Kumar Aggarwal, Angshul Majumdar |
| 2014 | ICPR | Matrix Recovery Using Split Bregman. | Anupriya Gogna, Ankita Shukla, Angshul Majumdar |