Mark Ibrahim
SOFTWARE ENGINEER | NEW YORK CITY, UNITED STATES
How do we encode our intuitive ability to recognize the same dog while it's jumping during the day or hiding behind a tree at night? Mark is interested in building representations of the factors of variation in the world around us. Mark is exploring how tools from areas such as topology, group theory, and equivariant architectures can shed light on how representations can improve interpretability, robustness, and data-efficiency (semi- or self-supervised settings).
Research Areas
Mark's Work
Mark's Publications
December 12, 2024
COMPUTER VISION
EvalGIM: A Library for Evaluating Generative Image Models
Melissa Hall, Oscar Mañas, Reyhane Askari, Mark Ibrahim, Candace Ross, Pietro Astolfi, Tariq Berrada Ifriqi, Marton Havasi, Yohann Benchetrit, Karen Ullrich, Carolina Braga, Abhishek Charnalia, Maeve Ryan, Mike Rabbat, Michal Drozdzal, Jakob Verbeek, Adriana Romero Soriano
December 12, 2024
July 24, 2024
COMPUTER VISION
X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
July 24, 2024
June 05, 2024
CORE MACHINE LEARNING
An Introduction to Vision-Language Modeling
Florian Bordes, Richard Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra
June 05, 2024
November 09, 2021
COMPUTER VISION
CORE MACHINE LEARNING
Grounding inductive biases in natural images: invariance stems from variations in data
Diane Bouchacourt, Mark Ibrahim, Ari Morcos
November 09, 2021
October 18, 2021
CORE MACHINE LEARNING
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten
October 18, 2021
September 23, 2020
ML APPLICATIONS
Neural Relational Autoregression for High-Resolution COVID-19 Forecasting
Maximilian Nickel, Levent Sagun, Mark Ibrahim, Matt Le, Timothee Lacroix
September 23, 2020
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