Wahid Bhimji

According to our database, Wahid Bhimji authored at least 29 papers between 2011 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

FAIR Universe Weak Lensing ML Uncertainty Challenge: Handling Uncertainties and Distribution Shifts for Precision Cosmology.

Biwei Dai, Po-Wen Chang, Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Ibrahim Elsharkawy, Steven Farrell, Isabelle Guyon, Christopher J. Harris, Elham E Khoda, Benjamin Nachman, David Rousseau, Uros Seljak, Ihsan Ullah, Yulei Zhang

CoRR, April, 2026

Competing with AI Scientists: Agent-Driven Approach to Astrophysics Research.

Thomas Borrett, Licong Xu, Andy Nilipour, Boris Bolliet, Sebastien Pierre, Erwan Allys, Celia Lecat, Biwei Dai, Po-Wen Chang, Wahid Bhimji

CoRR, April, 2026

Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials.

Alex Morehead, Miruna T. Cretu, Antonia Panescu, Rishabh Anand, Maurice Weiler, Tynan Perez, Samuel M. Blau, Steven Farrell, Wahid Bhimji, Anubhav Jain, Hrushikesh Sahasrabuddhe, Pietro Lio, Tommi S. Jaakkola, Rafael Gómez-Bombarelli, Rex Ying, N. Benjamin Erichson, Michael W. Mahoney

CoRR, February, 2026

2025

Deep learning the sources of MJO predictability: a spectral view of learned features.

Lin Yao, Da Yang, James P. C. Duncan, Ashesh Chattopadhyay, Pedram Hassanzadeh, Wahid Bhimji, Bin Yu

CoRR, October, 2025

FAIR Universe - HiggsML Uncertainty Challenge Public Dataset.

Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Po-Wen Chang, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Steven Farrell, Aishik Ghosh, Isabelle Guyon, Christopher J. Harris, Shih-Chieh Hsu, Elham E Khoda, Benjamin Nachman, Peter Nugent, David Rousseau, Ben Thorne, Ihsan Ullah, Yulei Zhang

Dataset, April, 2025

Building Machine Learning Challenges for Anomaly Detection in Science.

Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova, Wahid Bhimji, Wei-Lun Chao, Chris Harris, Shih-Chieh Hsu, Hilmar Lapp, Mark S. Neubauer, Josephine M. Namayanja, Aneesh Subramanian, Philip C. Harris, Advaith Anand, David Edward Carlyn, Subhankar Ghosh, Christopher G. Lawrence, Eric A. Moreno, Ryan Raikman, Jiaman Wu, Ziheng Zhang, Bayu Adhi, Mohammad Ahmadi Gharehtoragh, Saúl Alonso-Monsalve, Marta Babicz, Furqan Baig, Namrata Banerji, William Bardon, Tyler Barna, Tanya Y. Berger-Wolf, Adji Bousso Dieng, Micah Brachman, Quentin Buat, David C. Y. Hui, Phuong Cao, Franco Cerino, Yi-Chun Chang, Shivaji Chaulagain, An-Kai Chen, Deming Chen, Eric Chen, Chia-Jui Chou, Zih-Chen Ciou, Miles Cochran-Branson, Artur Cordeiro Oudot Choi, Michael Coughlin, Matteo Cremonesi, Maria Dadarlat, Peter Darch, Malina Desai, Daniel Diaz, Steven Dillmann, Javier M. Duarte, Isla Duporge, Urbas Ekka, Saba Entezari Heravi, Hao Fang, Rian Flynn, Geoffrey Fox, Emily Freed, Hang Gao, Jing Gao, Julia Gonski, Matthew J. Graham, Abolfazl Hashemi, Scott Hauck, James Hazelden, Joshua Henry Peterson, Duc Hoang, Wei Hu, Mirco Hünnefeld, David Hyde, Vandana P. Janeja, Nattapon Jaroenchai, Haoyi Jia, Yunfan Kang, Maksim Kholiavchenko, Elham E Khoda, Sangin Kim, Aditya Kumar, Bo-Cheng Lai, Trung Le, Chi-Wei Lee, JangHyeon Lee, Shaocheng Lee, Suzan van der Lee, Charles Lewis, Haitong Li, Haoyang Li, Henry Liao, Mia Liu, Xiaolin Liu, Xiulong Liu, Vladimir Loncar, Fangzheng Lyu, Ilya Makarov, Abhishikth Mallampalli Chen-Yu Mao, Alexander Michels, Alexander Migala, Farouk Mokhtar, Mathieu Morlighem

CoRR, March, 2025

Discriminative versus generative approaches to simulation-based inference.

Benjamin Sluijter, Sascha Diefenbacher, Wahid Bhimji, Benjamin Nachman

Mach. Learn. Sci. Technol., 2025

2024

FAIR Universe HiggsML Uncertainty Challenge Competition.

Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Steven Farrell, Aishik Ghosh, Isabelle Guyon, Chris Harris, Shih-Chieh Hsu, Elham E Khoda, Rémy Lyscar, Alexandre Michon, Benjamin Nachman, Peter Nugent, Mathis Reymond, David Rousseau, Benjamin Sluijter, Benjamin Thorne, Ihsan Ullah, Yulei Zhang

CoRR, 2024

Comprehensive Performance Modeling and System Design Insights for Foundation Models.

Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

Nine Months in the life of an all-flash file system.

Lisa Gerhardt, Stephen Simms, David Fox, Ershaad Basheer, Kirill Lozinskiy, Michael Moore, Wahid Bhimji

Proceedings of the Cray User Group, 2024

2023

Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access.

Wahid Bhimji, Dale W. Carder, Eli Dart, Javier M. Duarte, Ian Fisk, Robert W. Gardner, Chin Guok, Bo Jayatilaka, Tom Lehman, M. Lin, Carlos Maltzahn, Shawn McKee, Mark S. Neubauer, O. Rind, Oksana Shadura, N. V. Tran, P. van Gemmeren, Gordon Watts, B. A. Weaver, Frank Würthwein

Comput. Softw. Big Sci., December, 2023

High-level GPU code: a case study examining JAX and OpenMP.

Nestor Demeure, Theodore Kisner, Reijo Keskitalo, Rollin C. Thomas, Julian Borrill, Wahid Bhimji

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior.

Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence.

Ashesh Chattopadhyay, Jaideep Pathak, Ebrahim Nabizadeh, Wahid Bhimji, Pedram Hassanzadeh

CoRR, 2022

2021

The Petascale DTN Project: High Performance Data Transfer for HPC Facilities.

Eli Dart, William E. Allcock, Wahid Bhimji, Tim Boerner, Ravinderjeet Cheema, Andrew Cherry, Brent Draney, Salman Habib, Damian Hazen, Jason Hill, Matt Kollross, Suzanne Parete-Koon, Daniel Pelfrey, Adrian Pope, Jeff Porter, David Wheeler

CoRR, 2021

Architectural Requirements for Deep Learning Workloads in HPC Environments.

Khaled Z. Ibrahim, Tan Nguyen, Hai Ah Nam, Wahid Bhimji, Steven Farrell, Leonid Oliker, Michael Rowan, Nicholas J. Wright, Samuel Williams

Proceedings of the 2021 International Workshop on Performance Modeling, 2021

2020

A Pattern Recognition Algorithm for Quantum Annealers.

Frédéric Bapst, Wahid Bhimji, Paolo Calafiura, Heather M. Gray, Wim Lavrijsen, Lucy Linder, Alex Smith

Comput. Softw. Big Sci., December, 2020

2019

Etalumis: bringing probabilistic programming to scientific simulators at scale.

Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood

Proceedings of the International Conference for High Performance Computing, 2019

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.

Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.

Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood

CoRR, 2018

Interactive Distributed Deep Learning with Jupyter Notebooks.

Steven Andrew Farrell, Aaron Vose, Oliver Evans, Matthew L. Henderson, Shreyas Cholia, Fernando Pérez, Wahid Bhimji, Shane Canon, Rollin C. Thomas, Prabhat

Proceedings of the High Performance Computing, 2018

Graph Neural Networks for IceCube Signal Classification.

Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017

Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators.

Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat

CoRR, 2017

Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC.

Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth, Michela Paganini, Prabhat, Evan Racah

CoRR, 2017

Creating Virtual Universes Using Generative Adversarial Networks.

Mustafa Mustafa, Deborah Bard, Wahid Bhimji, Rami Al-Rfou, Zarija Lukic

CoRR, 2017

Deep learning at 15PF: supervised and semi-supervised classification for scientific data.

Thorsten Kurth, Jian Zhang, Nadathur Satish, Evan Racah, Ioannis Mitliagkas, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey

Proceedings of the International Conference for High Performance Computing, 2017

2016

PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures.

Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks.

Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2011

Establishing Applicability of SSDs to LHC Tier-2 Hardware Configuration

Samuel C. Skipsey, Wahid Bhimji, Mike Kenyon

CoRR, 2011