Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning

7 October 2022

Papers citing "Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning"

5 / 5 papers shown

Title
Deep multi-task mining Calabi-Yau four-folds Harold Erbin Riccardo Finotello Robin Schneider M. Tamaazousti 32 17 0 04 Aug 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,764 0 24 Feb 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 40 186 0 17 Feb 2021
Inception Neural Network for Complete Intersection Calabi-Yau 3-folds Harold Erbin Riccardo Finotello 43 27 0 27 Jul 2020
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 282 39,170 0 01 Sep 2014