Copertina

Constructing artificial life and materials scientists with accelerated AI using Deep AndersoNN

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Dajani, Saleem Abdul Fattah Ahmed Al, Keyes, David
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Applied Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Accelerating AI Performance using Anderson Extrapolation on GPUs
di: Dajani, Saleem Abdul Fattah Ahmed Al, et al.
Pubblicazione: (2024)

Noise as a probe of Majorana fermion surface states
di: Dajani, Saleem Al, et al.
Pubblicazione: (2022)

Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning
di: Bastawrous, Mary V., et al.
Pubblicazione: (2024)

DCIts -- Deep Convolutional Interpreter for time series
di: Horvatic, Davor, et al.
Pubblicazione: (2025)

Deep learning for the design of non-Hermitian topolectrical circuits
di: Chen, Xi, et al.
Pubblicazione: (2024)

Machine learning and atomic layer deposition: predicting saturation times from reactor growth profiles using artificial neural networks
di: Yanguas-Gil, Angel, et al.
Pubblicazione: (2022)

A Physics-informed Deep Operator for Real-Time Freeway Traffic State Estimation
di: Yu, Hongxin, et al.
Pubblicazione: (2025)

Bubble2Heat: Optical to Thermal Inference in Pool Boiling Using Physics-encoded Generative AI
di: Fu, Qianxi, et al.
Pubblicazione: (2025)

Accurate ignition detection of solid fuel particles using machine learning
di: Li, Tao, et al.
Pubblicazione: (2023)

DeepSeq: High-Throughput Single-Cell RNA Sequencing Data Labeling via Web Search-Augmented Agentic Generative AI Foundation Models
di: Dajani, Saleem A. Al, et al.
Pubblicazione: (2025)

Acoustic Structure Inverse Design and Optimization Using Deep Learning
di: Sun, Xuecong, et al.
Pubblicazione: (2021)

A fast sound power prediction tool for genset noise using machine learning
di: Pargal, Saurabh, et al.
Pubblicazione: (2025)

Physically Guided Deep Unsupervised Inversion for 1D Magnetotelluric Models
di: Goyes-Peñafiel, Paul, et al.
Pubblicazione: (2024)

The effect of dataset size and the process of big data mining for investigating solar-thermal desalination by using machine learning
di: Peng, Guilong, et al.
Pubblicazione: (2023)

Deep learning recognition and analysis of Volatile Organic Compounds based on experimental and synthetic infrared absorption spectra
di: Della Valle, Andrea, et al.
Pubblicazione: (2025)

In-situ surface porosity prediction in DED (directed energy deposition) printed SS316L parts using multimodal sensor fusion
di: Karthikeyan, Adithyaa, et al.
Pubblicazione: (2023)

Optimal Data Generation in Multi-Dimensional Parameter Spaces, using Bayesian Optimization
di: Mahani, M. R., et al.
Pubblicazione: (2023)

A Novel Proposal in Wind Turbine Blade Failure Detection: An Integrated Approach to Energy Efficiency and Sustainability
di: Abarca-Albores, Jordan, et al.
Pubblicazione: (2025)

CHLU: The Causal Hamiltonian Learning Unit as a Symplectic Primitive for Deep Learning
di: Jawahar, Pratik, et al.
Pubblicazione: (2026)

Deep Learning to Automate Parameter Extraction and Model Fitting of Two-Dimensional Transistors
di: Bennett, Robert K. A., et al.
Pubblicazione: (2025)

AI-Driven Discovery of High Performance Polymer Electrodes for Next-Generation Batteries
di: Ganti, Subhash V. S., et al.
Pubblicazione: (2025)

Leveraging KANs For Enhanced Deep Koopman Operator Discovery
di: Nehma, George, et al.
Pubblicazione: (2024)

Deep learning-enhanced dual-mode multiplexed optical sensor for point-of-care diagnostics of cardiovascular diseases
di: Han, Gyeo-Re, et al.
Pubblicazione: (2025)

Design of Resistive Frequency Selective Surface based Radar Absorbing Structure-A Deep Learning Approach
di: Sutrakar, Vijay Kumar, et al.
Pubblicazione: (2025)

An insertable glucose sensor using a compact and cost-effective phosphorescence lifetime imager and machine learning
di: Goncharov, Artem, et al.
Pubblicazione: (2024)

AIMBio-Mat: An AI-Native FAIR Platform for Closed-Loop Materials Discovery and Biomedical Translation
di: Mei, D. -M., et al.
Pubblicazione: (2026)

PICTS: A Novel Deep Reinforcement Learning Approach for Dynamic P-I Control in Scanning Probe Microscopy
di: Wei, Ziwei, et al.
Pubblicazione: (2025)

Multi-Task Deep Learning for Surface Metrology
di: Kucharski, D., et al.
Pubblicazione: (2025)

Machine Learning-Guided Design of Non-Reciprocal and Asymmetric Elastic Chiral Metamaterials
di: Yuan, Lingxiao, et al.
Pubblicazione: (2024)

Training all-mechanical neural networks for task learning through in situ backpropagation
di: Li, Shuaifeng, et al.
Pubblicazione: (2024)

Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures
di: Bond, R. Bailey, et al.
Pubblicazione: (2024)

Machine Learning-Assisted Thermoelectric Cooling for On-Demand Multi-Hotspot Thermal Management
di: Luo, Jiajian, et al.
Pubblicazione: (2024)

A rapid approach to urban traffic noise mapping with a generative adversarial network
di: Yang, Xinhao, et al.
Pubblicazione: (2024)

Training of Physical Neural Networks
di: Momeni, Ali, et al.
Pubblicazione: (2024)

Enhancing Multistep Prediction of Multivariate Market Indices Using Weighted Optical Reservoir Computing
di: Wang, Fang, et al.
Pubblicazione: (2024)

Empirical modeling and hybrid machine learning framework for nucleate pool boiling on microchannel structured surfaces
di: Kuberan, Vijay, et al.
Pubblicazione: (2025)

Uncertainty Reasoning with Photonic Bayesian Machines
di: Brückerhoff-Plückelmann, F., et al.
Pubblicazione: (2025)

PiGGO: Physics-Guided Learnable Graph Kalman Filters for Virtual Sensing of Nonlinear Dynamic Structures under Uncertainty
di: Haywood-Alexander, Marcus, et al.
Pubblicazione: (2026)

Weighted Bayesian Conformal Prediction
di: Lou, Xiayin, et al.
Pubblicazione: (2026)

ASPEN: An Adaptive Spectral Physics-Enabled Network for Ginzburg-Landau Dynamics
di: Chrisnanto, Julian Evan, et al.
Pubblicazione: (2025)