Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Harvard UniversityUS735 papers
- Massachusetts Institute of TechnologyUS455 papers
- University of OxfordGB379 papers
- University of ChicagoUS368 papers
- University of MichiganUS356 papers
- Lawrence Berkeley National LaboratoryUS354 papers
- The Ohio State UniversityUS350 papers
- Yale UniversityUS348 papers
- University of PittsburghUS317 papers
- Argonne National LaboratoryUS316 papers
- University College LondonGB312 papers
- University of PisaIT310 papers
8 papers · 2 filters
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data
Wai Tong Chung, Bassem Akoush, Pushan Sharma +9
Analysis of compressible turbulent flows is essential for applications related to propulsion, energy generation, and the environment. Here, we present BLASTNet 2.0, a 2.2 TB networ…
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang, Limei Wang, Jacob Helwig +60
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…
Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints
Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman +1
Prediction models have been widely adopted as the basis for decision-making in domains as diverse as employment, education, lending, and health. Yet, few real world problems readil…
Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions
Karine Karine, Predrag Klasnja, Susan A. Murphy +1
Just-in-Time Adaptive Interventions (JITAIs) are a class of personalized health interventions developed within the behavioral science community. JITAIs aim to provide the right typ…
Contextual Bandits with Budgeted Information Reveal
Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu +1
Contextual bandit algorithms are commonly used in digital health to recommend personalized treatments. However, to ensure the effectiveness of the treatments, patients are often re…
Arbitrary Decisions are a Hidden Cost of Differentially Private Training
Bogdan Kulynych, Hsiang Hsu, Carmela Troncoso +1
Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomizat…
THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression
Minghao Li, Ran Ben Basat, Shay Vargaftik +4
Deep neural networks (DNNs) are the de facto standard for essential use cases, such as image classification, computer vision, and natural language processing. As DNNs and datasets…
Complete Neural Networks for Complete Euclidean Graphs
Snir Hordan, Tal Amir, Steven J. Gortler +1
Neural networks for point clouds, which respect their natural invariance to permutation and rigid motion, have enjoyed recent success in modeling geometric phenomena, from molecula…