Efficient Power Allocation in Cooperative OFDM System with Channel Variation. - Morteza Ibrahimi; Ben Liang 001 (ICC, 2008)

Renewable, Time-Responsive DNA Logic Gates for Scalable Digital Circuits. - Ashish Goel; Morteza Ibrahimi (DNA, 2009)

Learning Networks of Stochastic Differential Equations. - José Bento 001; Morteza Ibrahimi; Andrea Montanari (NIPS, 2010)

Robust max-product belief propagation. - Morteza Ibrahimi; Adel Javanmard; Yashodhan Kanoria; Andrea Montanari (ACSCC, 2011)

Information theoretic limits on learning stochastic differential equations. - José Bento 001; Morteza Ibrahimi; Andrea Montanari (ISIT, 2011)

A renewable, modular, and time-responsive DNA circuit. - Ashish Goel; Morteza Ibrahimi (Nat. Comput., 2011)

Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems. - Morteza Ibrahimi; Adel Javanmard; Benjamin Van Roy (NIPS, 2012)

The set of solutions of random XORSAT formulae. - Morteza Ibrahimi; Yashodhan Kanoria; Matt Kraning; Andrea Montanari (SODA, 2012)

Support Recovery for the Drift Coefficient of High-Dimensional Diffusions. - José Bento Ayres Pereira; Morteza Ibrahimi (IEEE Trans. Inf. Theory, 2014)

Accelerated Time-of-Flight Mass Spectrometry. - Morteza Ibrahimi; Andrea Montanari; George S. Moore (IEEE Trans. Signal Process., 2014)

Hypermodels for Exploration. - Vikranth Dwaracherla; Xiuyuan Lu; Morteza Ibrahimi; Ian Osband; Zheng Wen 002; Benjamin Van Roy (ICLR, 2020)

On Efficiency in Hierarchical Reinforcement Learning. - Zheng Wen 002; Doina Precup; Morteza Ibrahimi; André Barreto 001; Benjamin Van Roy; Satinder Singh 001 (NeurIPS, 2020)

Epistemic Neural Networks. - Ian Osband; Zheng Wen 002; Mohammad Asghari; Morteza Ibrahimi; Xiyuan Lu; Benjamin Van Roy (CoRR, 2021)

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Botao Hao; Morteza Ibrahimi; Dieterich Lawson; Xiuyuan Lu; Brendan O'Donoghue; Benjamin Van Roy (CoRR, 2021)

The Neural Testbed: Evaluating Joint Predictions. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Xiuyuan Lu; Morteza Ibrahimi; Dieterich Lawson; Botao Hao; Brendan O'Donoghue; Benjamin Van Roy (NeurIPS, 2022)

Epistemic Neural Networks. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Morteza Ibrahimi; Xiuyuan Lu; Benjamin Van Roy (NeurIPS, 2023)

Approximate Thompson Sampling via Epistemic Neural Networks. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Morteza Ibrahimi; Xiuyuan Lu; Benjamin Van Roy (UAI, 2023)

Reinforcement Learning, Bit by Bit. - Xiuyuan Lu; Benjamin Van Roy; Vikranth Dwaracherla; Morteza Ibrahimi; Ian Osband; Zheng Wen 002 (Found. Trends Mach. Learn., 2023)