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

⚡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

Another video from a neural network has gone viral... on social networks 😄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

What’s this neural process?

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

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

📢📢📢 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

How ReLU neural network learns functions?

🚀 Excited to share our #ICLR2025 work on planning... with neural dynamics models! While our lab has developed diverse neural dynamics models for manipulating rigid, deformable, and granular objects, having the model alone doesn’t solve the problem—planning with it remains a challenge. 💡 Enter BaB-ND, led by Keyi and Jiangwei! We propose a scalable, GPU-accelerated branch-and-bound algorithm, inspired by neural network verification, to enable effective planning for diverse objects modeled with neural dynamics. 🔗 Project page (open-source + detailed docs!): 🎥 Watch the video to see T being pushed around obstacles, and check out Keyi’s thread for more details!show more

Helix neural network

#BestPaperAwardHonorableMention #SIGGRAPH2025 One neural PDE model, hundreds of cuts... and discontinuities — simulated in real time. 🚀 Introducing WindLifter: lifting the winding number fields lets us capture discontinuities in neural fields. Come see ChangYue’s talk today 👉show more