Predicting mechanical properties of polycrystalline nanopillars by interpretable machine learning by Teemu Koivisto, Marcin Mińkowski, Lasse Laurson

“…APL Machine Learning…”
Get full text

Polarization current-based reservoir computing utilizing an anti-ferroelectric-like HfZrO2 capacitor by Shin-Yi Min, Eishin Nako, Ryosho Nakane, Mitsuru Takenaka, Kasidit Toprasertpong, Shinichi Takagi

“…APL Machine Learning…”
Get full text

Dynamic in-context learning with conversational models for data extraction and materials property prediction by Chinedu E. Ekuma

“…APL Machine Learning…”
Get full text

Editorial: The intersection of machine learning and physical sciences: Insights from the 2024 Nobel Prizes by Gianluca Milano, Adnan Mehonic

“…APL Machine Learning…”
Get full text

Time to failure prediction for MLCCs: A machine learning approach based on leakage current data by Tianyu Jiang, Jincheng Qin, Faqiang Zhang, Mingcao Li, Xiaolian Yan, Mingsheng Ma, Yongxiang Li, Zhifu Liu

“…APL Machine Learning…”
Get full text

Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system by Philipp Teutsch, Philipp Pfeffer, Mohammad Sharifi Ghazijahani, Christian Cierpka, Jörg Schumacher, Patrick Mäder

“…APL Machine Learning…”
Get full text

PICL: Physics informed contrastive learning for partial differential equations by Cooper Lorsung, Amir Barati Farimani

“…APL Machine Learning…”
Get full text

Can ferroelectric tunnel junction be a game changer as eNVM and in neuromorphic hardware? by Sayani Majumdar

“…APL Machine Learning…”
Get full text

Modeling turbulent and self-gravitating fluids with Fourier neural operators by Keith Poletti, Stella S. R. Offner, Rachel A. Ward

“…APL Machine Learning…”
Get full text

Multi-objective Bayesian optimization of carbon nanotube yield and diameter control at synthesis by R. Waelder, W. Kim, M. A. Pitt, J. I. Myung, B. Maruyama

“…APL Machine Learning…”
Get full text

Waveflow: Boundary-conditioned normalizing flows applied to fermionic wave functions by Luca Thiede, Chong Sun, Alán Aspuru-Guzik

“…APL Machine Learning…”
Get full text

Memory technology enabling future computing systems by Paolo Fantini

“…APL Machine Learning…”
Get full text

Scalable recurrence graph network for stratifying RhoB texture dynamics in rectal cancer biopsies by Tuan D. Pham

“…APL Machine Learning…”
Get full text

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages by Irene Fang, Shobhan Roy, Phong Nguyen, Stephen Baek, H. S. Udaykumar

“…APL Machine Learning…”
Get full text

UniFIDES: Universal fractional integro-differential equations solver by Milad Saadat, Deepak Mangal, Safa Jamali

“…APL Machine Learning…”
Get full text

Accurate classification of materials with elEmBERT: Element embeddings for chemical benchmarks by Shokirbek Shermukhamedov, Dilorom Mamurjonova, Michael Probst

“…APL Machine Learning…”
Get full text

Data-driven approximations of topological insulator systems by Justin T. Cole, Michael J. Nameika

“…APL Machine Learning…”
Get full text

Deep learning for quantitative dynamic fragmentation analysis by Erwin Cazares, Brian E. Schuster

“…APL Machine Learning…”
Get full text

Large-scale-aware data augmentation for reduced-order models of high-dimensional flows by Philipp Teutsch, Mohammad Sharifi Ghazijahani, Florian Heyder, Christian Cierpka, Jörg Schumacher, Patrick Mäder

“…APL Machine Learning…”
Get full text

Morphology reconstruction from experimental small-angle x-ray scattering patterns by physics-aware neural network by Chenhao Zhao, Shenyang Sun, Xueqing Han, Jianhe Zhu, Wancheng Yu, Liangbin Li

“…APL Machine Learning…”
Get full text