Phys.org July 16, 2024 Understanding and interpreting dynamics of functional materials in situ is a challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. Although X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. A team of engineers in the US (Argonne National Laboratory, University of Chicago) developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. They demonstrated how […]
Tag Archives: Deep learning
2021’s Top Stories About AI Spoiler: A lot of them talked about what’s wrong with machine learning today
IEEE Spectrum December 27, 2021 Many of this year’s top articles grappled with the limits of deep learning and spotlighted researchers seeking new paths. Here are the 10 most popular AI articles that Spectrum published in 2021. Several came from Spectrum’s October 2021 special issue on AI, The Great AI Reckoning … read more.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – January 2019
Inside Big Data February 20, 2019 The articles are academic research papers, typically geared toward graduate students, post docs, and seasoned professionals. Articles are listed in no particular with a brief overview – Hard-Exploration Problems , Deep Neural Network Approximation for Custom Hardware: Where We’ve Been, Where We’re Going , Generating Textual Adversarial Examples for Deep Learning Models: A Survey , Revisiting Self-Supervised Visual Representation Learning , Self-Driving Cars: A Survey read more.