Ahmed Alaa

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 10

Top Topics

Machine Learning

Diffusion Models

Causal Inference

Discriminatively Trained

Top Venues

Discov. Artif. Intell.

Publications

Islam Al Sawi, Ahmed Alaa
Navigating the impact: a study of editors' and proofreaders' perceptions of AI tools in editing and proofreading. Discov. Artif. Intell. 4 (1) (2024)
Sungwoo Park, Dongjun Kim, Ahmed Alaa
Mean-field Chaos Diffusion Models. CoRR (2024)
Ahmed Alaa, Rachael V. Phillips, Emre Kiciman, Laura Balzer, Mark J. van der Laan, Maya Petersen
Large Language Models as Co-Pilots for Causal Inference in Medical Studies. CoRR (2024)
Jonathan W. Kim, Ahmed Alaa, Danilo Bernardo
EEG-GPT: Exploring Capabilities of Large Language Models for EEG Classification and Interpretation. CoRR (2024)
Ali Shirali, Alexander Schubert, Ahmed Alaa
Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care. CoRR (2023)
Ahmed Alaa, Zaid Ahmad, Mark J. van der Laan
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects. CoRR (2023)
Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. CoRR (2023)
Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR (2023)
Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi
Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS (2022)
Ahmed Alaa, Boris van Breugel, Evgeny S. Saveliev, Mihaela van der Schaar
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models. ICML (2022)