#physicsinformedmachinelearning search results
🚀 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗡𝗼𝘁𝗲𝘀 (𝗛𝗮𝗻𝗱𝘄𝗿𝗶𝘁𝘁𝗲𝗻 𝗣𝗗𝗙) Master the core of 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 —algorithms, models, training, evaluation & real-world examples. Perfect for interviews & AI enthusiasts! 🤖📊 📘FREE for the first 500 people! 1.…
If your truly serious about Antigravity Engineering, and find some information hard to grasp, keep reading and it will become Elementary reading someday. This Article introduces a Discrete Time Modeling that is very useful in CFD. You end up doing what this paper illustrates,…
Efficient training of neural networks is difficult. Our second Connectionism post introduces Modular Manifolds, a theoretical step toward more stable and performant training by co-designing neural net optimizers with manifold constraints on weight matrices.…
LLMs memorize a lot of training data, but memorization is poorly understood. Where does it live inside models? How is it stored? How much is it involved in different tasks? @jack_merullo_ & @srihita_raju's new paper examines all of these questions using loss curvature! (1/7)
⚡ Nikola Tesla was right. The universe isn’t solid — it vibrates. Quantum physics now shows reality is built not from matter, but from vibration and waves. Nikola Tesla once said, “If you want to find the secrets of the universe, think in terms of energy, frequency and…
Continual learning is largely a context compression problem. Compressing endless multimodal bitstreams into dense, reusable learning representations is crucial to deploying such systems in the real world. Building a unified learning representation will be necessary towards…
Sometimes I think we talk about AI like it only lives in chat boxes, but the real shift is happening out in the world in motion, not text. That’s why @openmind_agi stands out to me. They’re not just making robots smarter, they’re building the shared layer those robots can all…
to get started in mathematics for engineering, stop treating math as symbols; treat it as language for describing reality. begin with calculus; motion, change, flow. then linear algebra; systems, structure, control. then differential equations; dynamics, time, feedback. learn…
LLMにおいて同じ性能を出すのに必要なサイズが、約3ヶ月半ごとに半分になっている傾向を示す『密度化の法則』が「Nature Machine Intelligence」誌で発表されました。 同じ価格のチップで動かせるLLMの実質的な能力（能力密度）が、3ヶ月弱ごとに2倍になっている計算になります。…
Particle-Grid Neural Dynamics for Learning Deformable Object Models: A novel neural dynamics framework that learns to model the behavior of deformable objects directly from real-world observations, outperforming state-of-the-art simulators.
Why #AI Still Can’t Grasp Basic Physics Like Humans buff.ly/ADQpAMZ v/ @UniteAi #MachineLearning Cc @Delshur @jeancayeux @data_nerd @mdrechsler @gvalan @HeinzVHoenen @BroadenView
Mechanical Neural Network learns Addition through Gravity with pebbles achieves 91% accuracy! even has a learning rate, learns by adjusting the levers slightly each time :) source code in comment (not really a neural network tho, but kinda)
attempted to train a Spiking neural net from scratch again! this time it relies on repeated mutation-and-selection cycles to refine the connection weights. results at the bottom of post. Link to code in comment 50 neurons arranged in a 5×10 grid. Each neuron fires brief…
Engineers became the bottleneck when analyzing sensor data. MOVEdot (@movedot_) built AI agents that fix that, working hand in hand to analyze telemetry, video & documentation 100x faster. Starting with race cars, expanding to manufacturing, robotics, and more.…
We’re announcing a major advance in the study of fluid dynamics with AI 💧 in a joint paper with researchers from @BrownUniversity, @nyuniversity and @Stanford.
I've always loved the backstory of open-source libraries. From a user to a minor contributor! The first stable release is out! #DeepXDE #OpenSource #PhysicsInformedMachineLearning
The new 1 Trillion parameter Kimi K2 Thinking model runs well on 2 M3 Ultras in its native format - no loss in quality! The model was quantization aware trained (qat) at int4. Here it generated ~3500 tokens at 15 toks/sec using pipeline-parallelism in mlx-lm:
Physics - a branch of science where you use extremely long complicated formulas to explain why a ball rolls.
登上Nature子刊：清华发布Densing Law 密度定律，被称为大模型时代“摩尔定律” nature.com/articles/s4225… 模型能⼒密度随时间呈指数级增强，大模型能力密度每 3.5 个月翻一番！ 这代表模型会越来越小，能力会越来越强！代表模型“面壁小钢炮”MinicCPM~ Congrat @OpenBMB #nature #LLMs #MiniCPM #OpenAI
A Gentle Introduction to #Optimization ⬇️ amzn.to/3MQ6fE5 ————— #Mathematics #PrescriptiveAnalytics #ORMS #Analytics #AI #DataScience #ML #MachineLearning #Algorithms
🚀 #Trending #HotPaperAlert A Review of Physics-Informed Machine Learning in Fluid Mechanics 👉 brnw.ch/21wUycm #PhysicsInformedMachineLearning #PDEPreservedLearning #DeepNeuralNetwork #FluidMechanics #NavierStokes #mdpienergies #openaccess
#mdpienergies #highlycitedpaper A Review of Physics-Informed Machine Learning in Fluid Mechanics 👉ow.ly/uVvF50Qnhru #physicsinformedmachinelearning #PDEpreservedlearning #deepneuralnetwork #fluidmechanics #NavierStokes
📣 2nd workshop on Physics Enhancing ML in Applied Mechanics, 20/11/23, London & online @iop_conferences: program is out! 🎯 Free registration by 14/11 info: iop.eventsair.com/asm2023 🙏 reshare #phiML #scientificmachinelearning #physicsinformedMachineLearning #explainableML
📣 2nd workshop on Physics Enhancing Machine Learning in Applied Mechanics, 20 November 2023, London @iop_conferences 🎯 Free registration, hybrid event info: iop.eventsair.com/asm2023 🙏 reshare #phiML #scientificmachinelearning #physicsinformedMachineLearning #explainableML
I've always loved the backstory of open-source libraries. From a user to a minor contributor! The first stable release is out! #DeepXDE #OpenSource #PhysicsInformedMachineLearning
I've always loved the backstory of open-source libraries. From a user to a minor contributor! The first stable release is out! #DeepXDE #OpenSource #PhysicsInformedMachineLearning
🚀 #Trending #HotPaperAlert A Review of Physics-Informed Machine Learning in Fluid Mechanics 👉 brnw.ch/21wUycm #PhysicsInformedMachineLearning #PDEPreservedLearning #DeepNeuralNetwork #FluidMechanics #NavierStokes #mdpienergies #openaccess
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