An information theoretic technique for harnessing attenuation of high spatial frequencies to design ultra-high-density EEG. - Pulkit Grover; Jeffrey A. Weldon; Shawn K. Kelly; Praveen Venkatesh; Haewon Jeong (Allerton, 2015)

Is the direction of greater Granger causal influence the same as the direction of information flow? - Praveen Venkatesh; Pulkit Grover (Allerton, 2015)

Lower bounds on the minimax risk for the source localization problem. - Praveen Venkatesh; Pulkit Grover (ISIT, 2017)

An Information-Theoretic View of EEG Sensing. - Pulkit Grover; Praveen Venkatesh (Proc. IEEE, 2017)

Flexible Ultra-resolution Subdermal EEG Probes. - Zabir Ahmed; Jay W. Reddy; Kaustubh Deshpande; Ashwati Krishnan; Praveen Venkatesh; Shawn K. Kelly; Pulkit Grover; Maysamreza Chamanzar (BioCAS, 2018)

Low-Cost Carbon Fiber-Based Conductive Silicone Sponge EEG Electrodes. - Ashwati Krishnan; Ritesh Kumar; Praveen Venkatesh; Shawn K. Kelly; Pulkit Grover (EMBC, 2018)

Testing Changes in Communities for the Stochastic Block Model. - Aditya Gangrade; Praveen Venkatesh; Bobak Nazer; Venkatesh Saligrama (CoRR, 2018)

How should we define Information Flow in Neural Circuits? - Praveen Venkatesh; Sanghamitra Dutta; Pulkit Grover (ISIT, 2019)

Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models. - Aditya Gangrade; Praveen Venkatesh; Bobak Nazer; Venkatesh Saligrama (NeurIPS, 2019)

An Algorithm for Automated, Noninvasive Detection of Cortical Spreading Depolarizations Based on EEG Simulations. - Alireza Chamanzar; Shilpa Anna George; Praveen Venkatesh; Maysamreza Chamanzar; Lori Shutter; Jonathan Elmer; Pulkit Grover (IEEE Trans. Biomed. Eng., 2019)

An Information-Theoretic Quantification of Discrimination with Exempt Features. - Sanghamitra Dutta; Praveen Venkatesh; Piotr Mardziel; Anupam Datta; Pulkit Grover (AAAI, 2020)

How else can we define Information Flow in Neural Circuits? - Praveen Venkatesh; Sanghamitra Dutta; Pulkit Grover (ISIT, 2020)

Information Flow in Computational Systems. - Praveen Venkatesh; Sanghamitra Dutta; Pulkit Grover (IEEE Trans. Inf. Theory, 2020)

Can Information Flows Suggest Targets for Interventions in Neural Circuits? - Praveen Venkatesh; Sanghamitra Dutta; Neil Mehta; Pulkit Grover (NeurIPS, 2021)

Memory Guided Road Detection. - Praveen Venkatesh; Rwik Rana; Varun Jain (CoRR, 2021)

Analysis and Control of a Planar Quadrotor. - Praveen Venkatesh; Sanket Vadhvana; Varun Jain (CoRR, 2021)

Learning by Cheating : An End-to-End Zero Shot Framework for Autonomous Drone Navigation. - Praveen Venkatesh; Viraj Shah; Vrutik Shah; Yash Kamble; Joycee Mekie (CoRR, 2021)

Fast and Real-time End to End Control in Autonomous Racing Cars Through Representation Learning. - Praveen Venkatesh; Rwik Rana; Harish PM (CoRR, 2021)

Fairness Under Feature Exemptions: Counterfactual and Observational Measures. - Sanghamitra Dutta; Praveen Venkatesh; Piotr Mardziel; Anupam Datta; Pulkit Grover (IEEE Trans. Inf. Theory, 2021)

Extracting Unique Information Through Markov Relations. - Keerthana Gurushankar; Praveen Venkatesh; Pulkit Grover (Allerton, 2022)

Program Synthesis: Does Feedback Help? - Harsh M. Patel; Praveen Venkatesh; Shivam Sahni; Varun Jain; Mrinal Anand; Mayank Singh 001 (COMAD/CODS, 2022)

Indian Classical Music Synthesis. - Gaurav Viramgami; Hitarth Gandhi; Hrushti Naik; Nipun Mahajan; Praveen Venkatesh; Shivam Sahni; Mayank Singh 001 (COMAD/CODS, 2022)

Memory Guided Road Segmentation. - Praveen Venkatesh; Rwik Rana; Varun Jain (ICIAP (1), 2022)

Partial Information Decomposition via Deficiency for Multivariate Gaussians. - Praveen Venkatesh; Gabriel Schamberg (ISIT, 2022)

Quantifying Feature Contributions to Overall Disparity Using Information Theory. - Sanghamitra Dutta; Praveen Venkatesh; Pulkit Grover (CoRR, 2022)

Capturing and Interpreting Unique Information. - Praveen Venkatesh; Keerthana Gurushankar; Gabriel Schamberg (ISIT, 2023)

Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data. - Praveen Venkatesh; Corbett Bennett; Sam Gale; Tamina K. Ramirez; Greggory Heller; Severine Durand; Shawn R. Olsen; Stefan Mihalas (NeurIPS, 2023)

Foundation and large language models: fundamentals, challenges, opportunities, and social impacts. - Devon Myers; Rami Mohawesh; Venkata Ishwarya Chellaboina; Anantha Lakshmi Sathvik; Praveen Venkatesh; Yi-Hui Ho; Hanna Henshaw; Muna Al-Hawawreh; David Berdik; Yaser Jararweh (Clust. Comput., 2024)

Information-Theoretic Tools to Understand Distributed Source Coding in Neuroscience. - Ariel K. Feldman; Praveen Venkatesh; Douglas J. Weber; Pulkit Grover (IEEE J. Sel. Areas Inf. Theory, 2024)