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Physical Intuition

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Showing 1–35 of 35 papers

TitleStatusHype
Training Compute-Optimal Large Language ModelsCode6
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Generalizing Adam to Manifolds for Efficiently Training TransformersCode1
Constructing Custom Thermodynamics Using Deep LearningCode1
Physics-Inspired Distributed Radio Map EstimationCode1
InvDesFlow: An AI-driven materials inverse design workflow to explore possible high-temperature superconductorsCode1
Leveraging 2D Data to Learn Textured 3D Mesh GenerationCode1
MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledgeCode1
Automated Optical Multi-layer Design via Deep Reinforcement LearningCode0
Learning Physical Intuition of Block Towers by ExampleCode0
Meta-Learning for Stochastic Gradient MCMCCode0
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly DetectionCode0
Physics-tailored machine learning reveals unexpected physics in dusty plasmasCode0
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object StackingCode0
Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational AutoencodersCode0
Portfolio Cuts: A Graph-Theoretic Framework to Diversification—0
Towards understanding how attention mechanism works in deep learning—0
What is the Machine Learning?—0
Why is AI hard and Physics simple?—0
A Complete Recipe for Stochastic Gradient MCMC—0
Wind Park Power Prediction: Attention-Based Graph Networks and Deep Learning to Capture Wake Losses—0
Act the Part: Learning Interaction Strategies for Articulated Object Part Discovery—0
Advances in Bayesian Probabilistic Modeling for Industrial Applications—0
Analytical Modelling of Exoplanet Transit Specroscopy with Dimensional Analysis and Symbolic Regression—0
A Note on Spectral Map—0
Automated design of nonreciprocal thermal emitters via Bayesian optimization—0
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning—0
Biophysics at the coffee shop: lessons learned working with George Oster—0
Can Theoretical Physics Research Benefit from Language Agents?—0
Combining Machine Learning and Physics to Understand Glassy Systems—0
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial—0
Generalizable Features From Unsupervised Learning—0
Guiding Physical Intuition with Neural Stethoscopes—0
Large Language Models and Mathematical Reasoning Failures—0
Optimizing Cycle Life Prediction of Lithium-ion Batteries via a Physics-Informed Model—0
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