Targeted Dot Product Representation for Friend Recommendation in Online Social Networks. - Minh D. Dao; Akshay Rangamani; Sang Peter Chin; Nam P. Nguyen; Trac D. Tran (ASONAM, 2015)

Predicting local field potentials with recurrent neural networks. - Louis Y. Kim; Jacob Harer; Akshay Rangamani; James Moran; Philip D. Parks; Alik Widge; Emad N. Eskandar; Darin D. Dougherty; Sang (Peter) Chin (EMBC, 2016)

Critical Points Of An Autoencoder Can Provably Recover Sparsely Used Overcomplete Dictionaries. - Akshay Rangamani; Anirbit Mukherjee; Ashish Arora; Tejaswini Ganapathy; Amitabh Basu; Sang (Peter) Chin; Trac D. Tran (CoRR, 2017)

ChieF: A Change Pattern based Interpretable Failure Analyzer. - Dhaval Patel 002; Lam M. Nguyen; Akshay Rangamani; Shrey Shrivastava; Jayant Kalagnanam (IEEE BigData, 2018)

Reconstruction-Free Deep Convolutional Neural Networks for Partially Observed Images. - Arun Asokan Nair; Luoluo Liu; Akshay Rangamani; Peter Chin 001; Muyinatu A. Lediju Bell; Trac D. Tran (GlobalSIP, 2018)

A Greedy Pursuit Algorithm for Separating Signals from Nonlinear Compressive Observations. - Sang (Peter) Chin; Trac D. Tran; Dung N. Tran; Akshay Rangamani (ICASSP, 2018)

Sparse Coding and Autoencoders. - Akshay Rangamani; Anirbit Mukherjee; Amitabh Basu; Ashish Arora; Tejaswini Ganapathi; Sang (Peter) Chin; Trac D. Tran (ISIT, 2018)

Automated software vulnerability detection with machine learning. - Jacob A. Harer; Louis Y. Kim; Rebecca L. Russell; Onur Ozdemir; Leonard R. Kosta; Akshay Rangamani; Lei H. Hamilton; Gabriel I. Centeno; Jonathan R. Key; Paul M. Ellingwood; Marc W. McConley; Jeffrey M. Opper; et al. (CoRR, 2018)

A Scale Invariant Flatness Measure for Deep Network Minima. - Akshay Rangamani; Nam H. Nguyen; Abhishek Kumar; Dzung T. Phan; Sang H. Chin; Trac D. Tran (CoRR, 2019)

Deep Learning-Based Target Tracking and Classification for Low Quality Videos Using Coded Aperture Cameras. - Chiman Kwan; Bryan Chou; Jonathan Yang; Akshay Rangamani; Trac D. Tran; Jack Zhang; Ralph Etienne-Cummings (Sensors, 2019)

Target tracking and classification using compressive sensing camera for SWIR videos. - Chiman Kwan; Bryan Chou; Jonathan Yang; Akshay Rangamani; Trac D. Tran; Jack Zhang; Ralph Etienne-Cummings (Signal Image Video Process., 2019)

For interpolating kernel machines, the minimum norm ERM solution is the most stable. - Akshay Rangamani; Lorenzo Rosasco; Tomaso A. Poggio (CoRR, 2020)

Detection and Confirmation of Multiple Human Targets Using Pixel-Wise Code Aperture Measurements. - Chiman Kwan; David Gribben; Akshay Rangamani; Trac D. Tran; Jack Zhang; Ralph Etienne-Cummings (J. Imaging, 2020)

Neural-Guided, Bidirectional Program Search for Abstraction and Reasoning. - Simon Alford; Anshula Gandhi; Akshay Rangamani; Andrzej Banburski; Tony Wang; Sylee Dandekar; John Chin; Tomaso A. Poggio; Peter Chin 001 (COMPLEX NETWORKS, 2021)

A Scale Invariant Measure of Flatness for Deep Network Minima. - Akshay Rangamani; Nam H. Nguyen; Abhishek Kumar; Dzung T. Phan; Sang (Peter) Chin; Trac D. Tran (ICASSP, 2021)

Neural Collapse in Deep Homogeneous Classifiers and The Role of Weight Decay. - Akshay Rangamani; Andrzej Banburski-Fahey (ICASSP, 2022)

Feature learning in deep classifiers through Intermediate Neural Collapse. - Akshay Rangamani; Marius Lindegaard; Tomer Galanti; Tomaso A. Poggio (ICML, 2023)

On Generalization Bounds for Neural Networks with Low Rank Layers. - Andrea Pinto; Akshay Rangamani; Tomaso A. Poggio (ALT, 2025)

Low Rank and Sparse Fourier Structure in Recurrent Networks Trained on Modular Addition. - Akshay Rangamani (ICASSP, 2025)