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Physical Intuition

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Showing 1–25 of 35 papers

TitleStatusHype
Can Theoretical Physics Research Benefit from Language Agents?—0
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly DetectionCode0
Large Language Models and Mathematical Reasoning Failures—0
Physics-Inspired Distributed Radio Map EstimationCode1
Towards understanding how attention mechanism works in deep learning—0
A Note on Spectral Map—0
Automated design of nonreciprocal thermal emitters via Bayesian optimization—0
InvDesFlow: An AI-driven materials inverse design workflow to explore possible high-temperature superconductorsCode1
Optimizing Cycle Life Prediction of Lithium-ion Batteries via a Physics-Informed Model—0
MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledgeCode1
Physics-tailored machine learning reveals unexpected physics in dusty plasmasCode0
Constructing Custom Thermodynamics Using Deep LearningCode1
Generalizing Adam to Manifolds for Efficiently Training TransformersCode1
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning—0
Training Compute-Optimal Large Language ModelsCode6
Wind Park Power Prediction: Attention-Based Graph Networks and Deep Learning to Capture Wake Losses—0
Analytical Modelling of Exoplanet Transit Specroscopy with Dimensional Analysis and Symbolic Regression—0
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial—0
Act the Part: Learning Interaction Strategies for Articulated Object Part Discovery—0
Why is AI hard and Physics simple?—0
Automated Optical Multi-layer Design via Deep Reinforcement LearningCode0
Leveraging 2D Data to Learn Textured 3D Mesh GenerationCode1
Advances in Bayesian Probabilistic Modeling for Industrial Applications—0
Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational AutoencodersCode0
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