20 citations · 31 across the 9 of their papers we have counts for
10 papers
Continental-scale probabilistic resistivity imaging of Australia using deep learning: Implications for geology, groundwater, and critical minerals
Sihong Wu, Jiajia Sun, Jiefu Chen
Electrical resistivity is a fundamental physical property that provides powerful constraints on subsurface structure, lithology, fluid distribution, and mineralization. We present…
Direct Validation of Superconductivity through Contact-Free Detection of Persistent Supercurrents Using Room-Temperature Quantum Magnetometry
Xinyi Zeng, Chengzhen Qin, Bowen Fan +9
The accelerated emergence of new materials is driving the search for high temperature superconductors, but rapid experimental validation remains a critical bottleneck, particularly…
Insight Gained from Migrating a Machine Learning Model to Intelligence Processing Units
Hieu Le, Zhenhua He, Mai Le +5
The discoveries in this paper show that Intelligence Processing Units (IPUs) offer a viable accelerator alternative to GPUs for machine learning (ML) applications within the fields…
Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a Novel Probabilistic Transfer Learning Strategy
Wyatt Bridgman, Uma Balakrishnan, Reese Jones +5
In the field of surrogate modeling, polynomial chaos expansion (PCE) allows practitioners to construct inexpensive yet accurate surrogates to be used in place of the expensive forw…
Rational design of nanoscale stabilized oxide catalysts for OER with OC22
Richard Tran, Liqiang Huang, Yuan Zi +12
The efficiency of production via water electrolysis is typically limited to the sluggish oxygen evolution reaction (OER). As such, significant emphasis has been placed upon i…
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for Bayesian Inversion
Han Lu, Mohammad Khalil, Thomas Catanach +5
In the context of Bayesian inversion for scientific and engineering modeling, Markov chain Monte Carlo sampling strategies are the benchmark due to their flexibility and robustness…
First arrival picking using U-net with Lovasz loss and nearest point picking method
Pengyu Yuan, Wenyi Hu, Xuqing Wu +2
We proposed a robust segmentation and picking workflow to solve the first arrival picking problem for seismic signal processing. Unlike traditional classification algorithm, image…
Feasibility Analysis for the Problem of Active Near Field/Far Field Acoustic Pattern Synthesis in Free Space and Shallow Water Environments
Chaoxian Qi, Neil Jerome A. Egarguin, Daniel Onofrei +1
In this paper, a detailed sensitivity analysis of the active manipulation scheme for scalar Helmholtz fields proposed in our previous works, in both free space and constant-depth h…
Active manipulation of Helmholtz scalar fields: Near field synthesis with directional far field control
Neil Jerome A. Egarguin, Daniel Onofrei, Chaoxian Qi +1
In this article, we propose a strategy for the active manipulation of scalar Helmholtz fields in bounded near field regions of an active source while maintaining desired radiation…
Progressive transfer learning for low frequency data prediction in full waveform inversion
Wenyi Hu, Yuchen Jin, Xuqing Wu +1
For the purpose of effective suppression of the cycle-skipping phenomenon in full waveform inversion (FWI), we developed a Deep Neural Network (DNN) approach to predict the absent…