Nassar, Marcel

10 publications

NeurIPS 2025 PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Yan Wu, Esther Wershof, Sebastian M Schmon, Marcel Nassar, Błażej Osiński, Ridvan Eksi, Zichao Yan, Rory Stark, Kun Zhang, Thore Graepel

NeurIPS 2025 scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth T Gao, Akram Baharlouei, Kyra Thrush-Evensen, Nina Riehs, Amy F Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry E Miller, Ashley Mae Conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P Amini, Alex Xijie Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad

NeurIPSW 2024 PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Yan Wu, Esther Wershof, Sebastian M Schmon, Marcel Nassar, Błażej Osiński, Ridvan Eksi, Kun Zhang, Thore Graepel

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

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

TMLR 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

NeurIPSW 2022 Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Krzysztof Sadowski

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

ICLR 2020 Fully Convolutional Graph Neural Networks Using Bipartite Graph Convolutions Marcel Nassar, Xin Wang, Evren Tumer

NeurIPS 2017 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, Scott Gray, Stewart Hall, Luke Hornof, Amir Khosrowshahi, Carey Kloss, Ruby J Pai, Naveen Rao