A conceptual model for leaving the data-centric approach in machine learning

7 February 2023

Papers citing "A conceptual model for leaving the data-centric approach in machine learning"

6 / 6 papers shown

Title
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 97 520 0 09 Feb 2021
In Search of Lost Domain Generalization Ishaan Gulrajani David Lopez-Paz OOD 91 1,156 0 02 Jul 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 143 1,101 0 21 Feb 2020
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias Rachel K. E. Bellamy Kuntal Dey Michael Hind Samuel C. Hoffman Stephanie Houde ... Diptikalyan Saha P. Sattigeri Moninder Singh Kush R. Varshney Yunfeng Zhang FaML SyDa 101 810 0 03 Oct 2018
Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling Arka Daw Anuj Karpatne William Watkins J. Read Vipin Kumar PINN 50 536 0 31 Oct 2017
Domain Generalization via Invariant Feature Representation Krikamol Muandet David Balduzzi Bernhard Schölkopf OOD 142 1,185 0 10 Jan 2013