On noise-enhanced distributed inference in the presence of Byzantines. - Mukul Gagrani; Pranay Sharma; Satish G. Iyengar; V. Sriram Siddhardh Nadendla; Aditya Vempaty; Hao Chen 001; Pramod K. Varshney (Allerton, 2011)

Transmit and Receive Antenna Pairing in MIMO Relay Networks. - Mukul Gagrani; A. K. Chaturvedi (IEEE Commun. Lett., 2014)

Control of unknown linear systems with Thompson sampling. - Yi Ouyang 002; Mukul Gagrani; Rahul Jain 002 (Allerton, 2017)

Decentralized minimax control problems with partial history sharing. - Mukul Gagrani; Ashutosh Nayyar (ACC, 2017)

Learning Unknown Markov Decision Processes: A Thompson Sampling Approach. - Yi Ouyang 002; Mukul Gagrani; Ashutosh Nayyar; Rahul Jain 002 (NIPS, 2017)

Learning-based Control of Unknown Linear Systems with Thompson Sampling. - Yi Ouyang 002; Mukul Gagrani; Rahul Jain 002 (CoRR, 2017)

Scheduling and Estimation Strategies in a Sequential Networked Estimation Problem. - Mukul Gagrani; Marcos M. Vasconcelos; Ashutosh Nayyar (Allerton, 2018)

Thompson Sampling for some decentralized control problems. - Mukul Gagrani; Ashutosh Nayyar (CDC, 2018)

Regret Analysis for Learning in a Multi-Agent Linear-Quadratic Control Problem. - Seyed Mohammad Asghari; Mukul Gagrani; Ashutosh Nayyar (ACC, 2020)

Weakly Coupled Constrained Markov Decision Processes in Borel Spaces. - Mukul Gagrani; Ashutosh Nayyar (ACC, 2020)

Posterior Sampling-Based Reinforcement Learning for Control of Unknown Linear Systems. - Yi Ouyang 002; Mukul Gagrani; Rahul Jain 002 (IEEE Trans. Autom. Control., 2020)

Optimal Scheduling Strategy for Networked Estimation With Energy Harvesting. - Marcos M. Vasconcelos; Mukul Gagrani; Ashutosh Nayyar; Urbashi Mitra (IEEE Trans. Control. Netw. Syst., 2020)

Thompson sampling for linear quadratic mean-field teams. - Mukul Gagrani; Sagar Sudhakara; Aditya Mahajan; Ashutosh Nayyar; Yi Ouyang 002 (CDC, 2021)

A relaxed technical assumption for posterior sampling-based reinforcement learning for control of unknown linear systems. - Mukul Gagrani; Sagar Sudhakara; Aditya Mahajan; Ashutosh Nayyar; Yi Ouyang 002 (CoRR, 2021)

Worst-Case Guarantees for Remote Estimation of an Uncertain Source. - Mukul Gagrani; Yi Ouyang 002; Mohammad Rasouli 001; Ashutosh Nayyar (IEEE Trans. Autom. Control., 2021)

A modified Thompson sampling-based learning algorithm for unknown linear systems. - Mukul Gagrani; Sagar Sudhakara; Aditya Mahajan; Ashutosh Nayyar; Yi Ouyang 002 (CDC, 2022)

Neural Topological Ordering for Computation Graphs. - Mukul Gagrani; Corrado Rainone; Yang Yang; Harris Teague; Wonseok Jeon; Roberto Bondesan; Herke van Hoof; Christopher Lott; Weiliang Will Zeng; Piero Zappi (NeurIPS, 2022)

Neural DAG Scheduling via One-Shot Priority Sampling. - Wonseok Jeon; Mukul Gagrani; Burak Bartan; Weiliang Will Zeng; Harris Teague; Piero Zappi; Christopher Lott (ICLR, 2023)

Recursive Speculative Decoding: Accelerating LLM Inference via Sampling Without Replacement. - Wonseok Jeon; Mukul Gagrani; Raghavv Goel; Junyoung Park; Mingu Lee; Christopher Lott (CoRR, 2024)

Direct Alignment of Draft Model for Speculative Decoding with Chat-Fine-Tuned LLMs. - Raghavv Goel; Mukul Gagrani; Wonseok Jeon; Junyoung Park; Mingu Lee; Christopher Lott (CoRR, 2024)

On Speculative Decoding for Multimodal Large Language Models. - Mukul Gagrani; Raghavv Goel; Wonseok Jeon; Junyoung Park; Mingu Lee; Christopher Lott (CoRR, 2024)

CAOTE: KV Caching through Attention Output Error based Token Eviction. - Raghavv Goel; Junyoung Park; Mukul Gagrani; Dalton Jones; Matthew J. Morse; Harper Langston; Mingu Lee; Christopher Lott (CoRR, 2025)

VOCABTRIM: Vocabulary Pruning for Efficient Speculative Decoding in LLMs. - Raghavv Goel; Sudhanshu Agrawal; Mukul Gagrani; Junyoung Park; Yifan Zao; He Zhang; Tian Liu; Yiping Yang; Xin Yuan; Jiuyan Lu; Chris Lott; Mingu Lee (CoRR, 2025)