Mitigating near-field interference in laptop embedded wireless transceivers. - Marcel Nassar; Kapil Gulati; Arvind K. Sujeeth; Navid Aghasadeghi; Brian L. Evans; Keith R. Tinsley (ICASSP, 2008)

A new multitask learning method for multiorganism gene network estimation. - Marcel Nassar; Rami Abdallah; Hady Ali Zeineddine; Elias Yaacoub; Zaher Dawy (ISIT, 2008)

Low complexity EM-based decoding for OFDM systems with impulsive noise. - Marcel Nassar; Brian L. Evans (ACSCC, 2011)

Non-Parametric Impulsive Noise Mitigation in OFDM Systems Using Sparse Bayesian Learning. - Jing Lin 002; Marcel Nassar; Brian L. Evans (GLOBECOM, 2011)

Statistical Modeling of Asynchronous Impulsive Noise in Powerline Communication Networks. - Marcel Nassar; Kapil Gulati; Yousof Mortazavi; Brian L. Evans (GLOBECOM, 2011)

Stochastic Modeling of Microwave Oven Interference in WLANs. - Marcel Nassar; Xintian Eddie Lin; Brian L. Evans (ICC, 2011)

A multiorganism based method for Bayesian gene network estimation. - Zaher Dawy; Elias Yaacoub; Marcel Nassar; Rami Abdallah; Hady Ali Zeineddine (Biosyst., 2011)

Mitigating Near-field Interference in Laptop Embedded Wireless Transceivers. - Marcel Nassar; Kapil Gulati; Marcus R. DeYoung; Brian L. Evans; Keith R. Tinsley (J. Signal Process. Syst., 2011)

Cyclostationary noise modeling in narrowband powerline communication for Smart Grid applications. - Marcel Nassar; Anand Dabak; Il Han Kim; Tarkesh Pande; Brian L. Evans (ICASSP, 2012)

Adaptive experimental design for drug combinations. - Mijung Park; Marcel Nassar; Brian L. Evans; Haris Vikalo (SSP, 2012)

Active Bayesian Optimization: Minimizing Minimizer Entropy - Il Memming Park; Marcel Nassar; Mijung Park (CoRR, 2012)

Local Utility Power Line Communications in the 3-500 kHz Band: Channel Impairments, Noise, and Standards. - Marcel Nassar; Jing Lin 002; Yousof Mortazavi; Anand G. Dabak; Il Han Kim; Brian L. Evans (IEEE Signal Process. Mag., 2012)

A factor-graph approach to joint OFDM channel estimation and decoding in impulsive noise channels. - Marcel Nassar; Phil Schniter; Brian L. Evans (ACSSC, 2013)

FPGA implementation of a message-passing OFDM receiver for impulsive noise channels. - Karl F. Nieman; Marcel Nassar; Jing Lin 002; Brian L. Evans (ACSSC, 2013)

Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning. - Jing Lin 002; Marcel Nassar; Brian L. Evans (IEEE J. Sel. Areas Commun., 2013)

Bayesian Active Learning for Drug Combinations. - Mijung Park; Marcel Nassar; Haris Vikalo (IEEE Trans. Biomed. Eng., 2013)

A Factor Graph Approach to Joint OFDM Channel Estimation and Decoding in Impulsive Noise Environments. - Marcel Nassar; Philip Schniter; Brian L. Evans (IEEE Trans. Signal Process., 2014)

Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks. - Urs Köster; Tristan Webb; Xin Wang; Marcel Nassar; Arjun K. Bansal; William Constable; Oguz Elibol; Stewart Hall; Luke Hornof; Amir Khosrowshahi; Carey Kloss; Ruby J. Pai; et al. (NIPS, 2017)

Flexpoint: Predictive Numerics for Deep Learning. - Valentina Popescu; Marcel Nassar; Xin Wang; Evren Tumer; Tristania Webb (ARITH, 2018)

Hierarchical Bipartite Graph Convolution Networks. - Marcel Nassar (CoRR, 2018)

Conditional Graph Neural Processes: A Functional Autoencoder Approach. - Marcel Nassar; Xin Wang; Evren Tumer (CoRR, 2018)

Structured Citation Trend Prediction Using Graph Neural Networks. - Daniel Cummings; Marcel Nassar (ICASSP, 2020)

Permutohedral-GCN: Graph Convolutional Networks with Global Attention. - Hesham Mostafa; Marcel Nassar (CoRR, 2020)

Connection Management xAPP for O-RAN RIC: A Graph Neural Network and Reinforcement Learning Approach. - Oner Orhan; Vasuki Narasimha Swamy; Thomas Tetzlaff; Marcel Nassar; Hosein Nikopour; Shilpa Talwar (ICMLA, 2021)

Implicit SVD for Graph Representation Learning. - Sami Abu-El-Haija; Hesham Mostafa; Marcel Nassar; Valentino Crespi; Greg Ver Steeg; Aram Galstyan (NeurIPS, 2021)

On Local Aggregation in Heterophilic Graphs. - Hesham Mostafa; Marcel Nassar; Somdeb Majumdar (CoRR, 2021)

IAB Topology Design: A Graph Embedding and Deep Reinforcement Learning Approach. - Meryem Simsek; Oner Orhan; Marcel Nassar; Oguz Elibol; Hosein Nikopour (IEEE Commun. Lett., 2021)

Technology Growth Ranking Using Temporal Graph Representation Learning. - Daniel Cummings; Ashrita Brahmaroutu; Marcel Nassar; Nesreen K. Ahmed (WWW (Companion Volume), 2022)

Generative Graph Augmentation for Minority Class in Fraud Detection. - Lin Meng; Hesham Mostafa; Marcel Nassar; Xiaonan Zhang 001; Jiawei Zhang 001 (CIKM, 2023)

Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. - Shengyu Feng; Hesham Mostafa; Marcel Nassar; Somdeb Majumdar; Subarna Tripathi (WACV, 2023)

MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling. - Kin Long Kelvin Lee; Carmelo Gonzales; Marcel Nassar; Matthew Spellings; Mikhail Galkin 001; Santiago Miret (CoRR, 2023)

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science. - Santiago Miret; Kin Long Kelvin Lee; Carmelo Gonzales; Marcel Nassar; Matthew Spellings (Trans. Mach. Learn. Res., 2023)

Pretraining Graph Neural Networks for Few-Shot Analog Circuit Modeling and Design. - Kourosh Hakhamaneshi; Marcel Nassar; Mariano Phielipp; Pieter Abbeel; Vladimir Stojanovic (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis. - Yan Wu; Esther Wershof; Sebastian M. Schmon; Marcel Nassar; Blazej Osinski; Ridvan Eksi; Kun Zhang; Thore Graepel (CoRR, 2024)