Marcel Nassar

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 23

Top Topics

Graph Representation

Reinforcement Learning

Impulsive Noise

Top Venues

IEEE Commun. Lett.

IEEE Trans. Signal Process.

Publications

Kourosh Hakhamaneshi, Marcel Nassar, Mariano Phielipp, Pieter Abbeel, Vladimir Stojanovic
Pretraining Graph Neural Networks for Few-Shot Analog Circuit Modeling and Design. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (7) (2023)
Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings, Mikhail Galkin, Santiago Miret
MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling. CoRR (2023)
Lin Meng, Hesham Mostafa, Marcel Nassar, Xiaonan Zhang, Jiawei Zhang
Generative Graph Augmentation for Minority Class in Fraud Detection. CIKM (2023)
Shengyu Feng, Hesham Mostafa, Marcel Nassar, Somdeb Majumdar, Subarna Tripathi
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. WACV (2023)
Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science. Trans. Mach. Learn. Res. 2023 (2023)
Kourosh Hakhamaneshi, Marcel Nassar, Mariano Phielipp, Pieter Abbeel, Vladimir Stojanovic
Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design. CoRR (2022)
Daniel Cummings, Ashrita Brahmaroutu, Marcel Nassar, Nesreen K. Ahmed
Technology Growth Ranking Using Temporal Graph Representation Learning. WWW (Companion Volume) (2022)
Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science. CoRR (2022)
Oner Orhan, Vasuki Narasimha Swamy, Thomas Tetzlaff, Marcel Nassar, Hosein Nikopour, Shilpa Talwar
Connection Management xAPP for O-RAN RIC: A Graph Neural Network and Reinforcement Learning Approach. CoRR (2021)
Daniel Cummings, Marcel Nassar
Structured Citation Trend Prediction Using Graph Neural Networks. CoRR (2021)
Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Implicit SVD for Graph Representation Learning. NeurIPS (2021)
Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Implicit SVD for Graph Representation Learning. CoRR (2021)
Oner Orhan, Vasuki Narasimha Swamy, Thomas Tetzlaff, Marcel Nassar, Hosein Nikopour, Shilpa Talwar
Connection Management xAPP for O-RAN RIC: A Graph Neural Network and Reinforcement Learning Approach. ICMLA (2021)
Hesham Mostafa, Marcel Nassar, Somdeb Majumdar
On Local Aggregation in Heterophilic Graphs. CoRR (2021)
Meryem Simsek, Oner Orhan, Marcel Nassar, Oguz Elibol, Hosein Nikopour
IAB Topology Design: A Graph Embedding and Deep Reinforcement Learning Approach. IEEE Commun. Lett. 25 (2) (2021)
Shengyu Feng, Subarna Tripathi, Hesham Mostafa, Marcel Nassar, Somdeb Majumdar
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. CoRR (2021)
Daniel Cummings, Marcel Nassar
Structured Citation Trend Prediction Using Graph Neural Networks. ICASSP (2020)
Hesham Mostafa, Marcel Nassar
Permutohedral-GCN: Graph Convolutional Networks with Global Attention. CoRR (2020)
Valentina Popescu, Marcel Nassar, Xin Wang, Evren Tumer, Tristania Webb
Flexpoint: Predictive Numerics for Deep Learning. ARITH (2018)
Marcel Nassar
Hierarchical Bipartite Graph Convolution Networks. CoRR (2018)
Marcel Nassar, Xin Wang, Evren Tumer
Conditional Graph Neural Processes: A Functional Autoencoder Approach. CoRR (2018)
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, Naveen Rao
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks. CoRR (2017)
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, Naveen Rao
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks. NIPS (2017)
Marcel Nassar, Philip Schniter, Brian L. Evans
A Factor Graph Approach to Joint OFDM Channel Estimation and Decoding in Impulsive Noise Environments. IEEE Trans. Signal Process. 62 (6) (2014)
Jing Lin, Marcel Nassar, Brian L. Evans
Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning. IEEE J. Sel. Areas Commun. 31 (7) (2013)
Mijung Park, Marcel Nassar, Haris Vikalo
Bayesian Active Learning for Drug Combinations. IEEE Trans. Biomed. Eng. 60 (11) (2013)
Jing Lin, Marcel Nassar, Brian L. Evans
Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning CoRR (2013)
Marcel Nassar, Philip Schniter, Brian L. Evans
A Factor Graph Approach to Joint OFDM Channel Estimation and Decoding in Impulsive Noise Environments. CoRR (2013)
Karl F. Nieman, Marcel Nassar, Jing Lin, Brian L. Evans
FPGA implementation of a message-passing OFDM receiver for impulsive noise channels. ACSSC (2013)
Marcel Nassar, Phil Schniter, Brian L. Evans
A factor-graph approach to joint OFDM channel estimation and decoding in impulsive noise channels. ACSSC (2013)
Mijung Park, Marcel Nassar, Brian L. Evans, Haris Vikalo
Adaptive experimental design for drug combinations. SSP (2012)
Il Memming Park, Marcel Nassar, Mijung Park
Active Bayesian Optimization: Minimizing Minimizer Entropy CoRR (2012)
Marcel Nassar, Jing Lin, Yousof Mortazavi, Anand G. Dabak, Il Han Kim, Brian L. Evans
Local Utility Power Line Communications in the 3-500 kHz Band: Channel Impairments, Noise, and Standards. IEEE Signal Process. Mag. 29 (5) (2012)
Marcel Nassar, Anand Dabak, Il Han Kim, Tarkesh Pande, Brian L. Evans
Cyclostationary noise modeling in narrowband powerline communication for Smart Grid applications. ICASSP (2012)
Jing Lin, Marcel Nassar, Brian L. Evans
Non-Parametric Impulsive Noise Mitigation in OFDM Systems Using Sparse Bayesian Learning. GLOBECOM (2011)
Marcel Nassar, Brian L. Evans
Low complexity EM-based decoding for OFDM systems with impulsive noise. ACSCC (2011)
Marcel Nassar, Kapil Gulati, Marcus R. DeYoung, Brian L. Evans, Keith R. Tinsley
Mitigating Near-field Interference in Laptop Embedded Wireless Transceivers. J. Signal Process. Syst. 63 (1) (2011)
Marcel Nassar, Xintian E. Lin, Brian L. Evans
Stochastic Modeling of Microwave Oven Interference in WLANs. ICC (2011)
Marcel Nassar, Kapil Gulati, Yousof Mortazavi, Brian L. Evans
Statistical Modeling of Asynchronous Impulsive Noise in Powerline Communication Networks. GLOBECOM (2011)
Zaher Dawy, Elias Yaacoub, Marcel Nassar, Rami Abdallah, Hady Ali Zeineddine
A multiorganism based method for Bayesian gene network estimation. Biosyst. 103 (3) (2011)
Marcel Nassar, Rami Abdallah, Hady Ali Zeineddine, Elias Yaacoub, Zaher Dawy
A new multitask learning method for multiorganism gene network estimation. ISIT (2008)
Marcel Nassar, Kapil Gulati, Arvind K. Sujeeth, Navid Aghasadeghi, Brian L. Evans, Keith R. Tinsley
Mitigating near-field interference in laptop embedded wireless transceivers. ICASSP (2008)