Introducing Neural Developmental Programs (NDPs)🧬🧠Instead of neural networks with... fixed architectures, we allow neural networks to grow through a dynamic self-organizing process, inspired by how biological nervous systems develop👇 PDF:show more

neural networks are truly amazing

New article! A visual, interactive intro to Neural Networks,... backprop, and more! I hope the easiest resource to learn Neural Networks! #Datavisualization #dataviz #RStats #DataScience #scicomm #svelte #d3js #MachineLearning #aishow more

⚡Physics-Informed Neural Networks (PINN)⚡ PINNs are neural networks that... are trained to solve supervised learning tasks while respecting any given laws of physics described by general nonlinear partial differential equations. 👉 Full Tutorial:show more

Déda et al. use neural networks for flow analysis... & control in nonlinear fluid systems, showcasing accuracy & stabilization in complex dynamics. From the Lorenz system to confined cylinder flows, neural networks shine as effective models & controllers.show more

Visualization of what is inside of AI models. This... represents the layers of interconnected neural networks. And yes patterns do develop and they can form a signature of how they think. The pattern can be seen as the thought process.show more

New paper: We present a "Unified Neural Scaling Law"... functional form that accurately models & extrapolates the multivariate scaling behaviors of artificial neural networks as the variables listed in this attached video are varied. (1/N)show more

General relativity 🤝 neural fields This simulation of a... black hole is coming from our neural networks 🚀 We introduce Einstein Fields, a compact NN representation for 4D numerical relativity. EinFields are designed to handle the tensorial properties of GR and its derivatives.show more

Impressive work from Jianping Fu University of Michigan Orly... Reiner's Lab Song and Ming Labs describing a new method to grow a bona fide neural tube from human stem cells. NT-like structures develop antero posterior & dorso-ventral polarities as in a normal neural tube, including hox gene segmentation & Neural crest cells. Great tool to study neuronal specificationshow more

2 robots with individual neural networks putting away unseen... groceries (zero shot) Our AI progress is accelerating Figure's timeline for home robotsshow more

Imagine: Parallel Neural Networks with Shaders 🤔 (GLSL instead... of CUDA) Parallelization by encoding the weights and activations as Buffer Objects or Textures, using fs to perform matmul and activation functions in parallel. Each fragm shader instance parproc 1..n neuron.show more

🚨New lecture note 🚨 🧵1) Neural networks tend to... learn low frequencies first, and only later the high-frequency oscillations, if at all. Left panel: training data and the neural-net fit. Right panel: their Fourier transforms. code:show more

This project argues that latent space—the learned, multidimensional, representational... substrate of neural networks—is not only a mathematical construct but, read through literature, a structure akin to architectural interiority that renders the abstract physically legible.show more

Day 12 of learning AI bs from scratch >... a look into recurrent neural networks (RNN's) > learned about Long Short-Term Memory > read couple chapters of > drawbacks of RNN's > Simple Neural networks → CNN → RNN will try and train one MLP, CNN and a RNN from scratch next and try and summarize its working it a blog. back to doing based learning after this, much more retention like that.show more

📢📢📢 NoKSR: Kernel-Free Neural Surface Reconstruction via Point Cloud... Serialization #3DV2025 TL;DR: neural reconstruction with a simpler architecture (no linear systems to solve), and up to 3x speedup vs. voxel-based methods!show more

1. Machine Learning Specialization. Break Into AI with this... 3-course program by Andrew Ng. What You’ll learn: → Build ML models → Train neural networks → Deep reinforcement learning → Unsupervised learning techniques 🔗show more

1. Machine Learning Specialization Break into AI with this... 3-course program by Andrew Ng. What you’ll learn: → Build machine learning models → Train neural networks → Deep reinforcement learning → Unsupervised learning techniques 🔗show more

#SIGGRAPHAsia2024 🔥 Replace your Marching Cubes code with our... Occupancy-Based Dual Contouring to reveal the "real" shape from either a signed distance function or an occupancy function. No neural networks involved. Web:show more