#spatialautoregressivemodel 搜索结果

WorldVLA: Towards Autoregressive Action World Model Paper: arxiv.org/abs/2506.21539 Code: github.com/alibaba-damo-a… Work from Alibaba to integrate VLA model and world model into one single autoregressive framework. The resulting action world model can predict both future images…

The most important geospatial concept? Spatial Autocorrelation. It can make the difference between spurious and accurate results. Here’s what you need to know about it:

🚨 The era of infinite internet data is ending, So we ask: 👉 What’s the right generative modelling objective when data—not compute—is the bottleneck? TL;DR: ▶️Compute-constrained? Train Autoregressive models ▶️Data-constrained? Train Diffusion models Get ready for 🤿 1/n

So these researchers figured out you can basically hallucinate 3D cities into existence using just satellite photos & a diffusion model. The problem's pretty straightforward: satellites only see rooftops. Building facades? Invisible. Street-level detail? Doesn't exist. But…

🚨 $ASTS DISRUPTIVE 3D CHESS 🚨 A tweet about: Orthogonal enabling dimensions of the intelligent-network continuum, AKA Mutually catalytic complements, these three: AI ✖️ D2C NTN ✖️ Cohere OTFS They’re orthogonal in physics but 👉multiplicative👈 in economics. 🐾

🚀 We release SpatialTrackerV2: the first feedforward model for dynamic 3D reconstruction and 3D point tracking — all at once! Reconstruct dynamic scenes and predict pixel-wise 3D motion in seconds. 🔗 Webpage: spatialtracker.github.io 🔍 Online Demo: huggingface.co/spaces/Yuxihen…

🚀 Introducing scGPT-spatial! 🧬🌍 A game-changing spatial-omic foundation model, built on the powerful scGPT framework with MoE (mixture of experts) and continually pretrained on a massive 30 million spatial single-cell profiles! 🧠 What’s the challenge? Spatial…

Every street, farm & river holds untold stories. With Deepspatial’s GeoAI, turn data into intelligence, make smarter decisions & unlock growth everywhere. Understand your environment—enable limitless possibilities. #Deepspatial #DataDriven $DSAI $DSAIF $DSAI.CN

How do you build a geospatial AI roadmap that actually works? 👀 AI adoption is growing fast, but most teams still miss its full spatial potential. Our latest post shares a 5-step roadmap for bringing AI safely into your spatial workflows. Read more:hubs.ly/Q03PRl6V0

Riise et al., "Visual Autoregressive Models Beat Diffusion Models on Inference Time Scaling" Beam search with Autoregressive image generators with verifiers.

Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Contributions: • We propose STORM, the first feed-forward, self-supervised method for fast and accurate reconstruction of dynamic 3D scenes from sparse, multi-timestep, posed camera images. • Our bottom-up…

🛰 Introducing STAR.VISION Super-Resolution Algorithm (SV-SkipDiffusion-SR) 🌍 At , we’ve developed an innovative diffusion-based super-resolution algorithm that enhances satellite image resolution, revealing finer textures and sharper details…

SatMAE : Pre-training Transformers with Temporal and Multi-Spectral Satellite Imagery - MAE based self-supervised learning framework focusing on Satellite imagery - Leverage temporal and multispectral information through encoding - Introduces Independent Masking and Inconsistent…

✨ Train language models directly on continuous data - without tokenization ✨ We propose an easy way to train GPT-style autoregressive models on continuous data, without error accumulation. We test it on audio 🔊, but this method can easily work with other modalities 🎆 👇🧵

🧠 SASI Models: AI That Thinks Like Us 🤖✨ What if AI could understand data, not just process it? SASI (Spatial Adaptive Semantic Inference) models combine adaptive learning + semantic understanding for smarter AI. 🌐🔍 🔹 How? Uses spatial & semantic connections. 🔹 Why?…

We're excited to highlight ShiftedBetaGeoModel (sBG) in PyMC-Marketing v0.17.0! Predict customer retention, model cohorts, and make smarter CLV-driven decisions — all with a single Bayesian model 🧩 Check it out: dub.link/EoYryvG #PyMC #CohortAnalysis #CustomerAnalytics

New blog post! bartwronski.com/2019/09/22/loc… Local linear models and guided filter - an alternative to (joint) bilateral filtering. While I use an example of SSAO, it applies to anything - SSRR, GI, or even more to stochastic and inherently noisy raytracing!

⚡️ Last chapter in my Spatial Statistics book! ⚡️ Spatial point process modeling: - Log-Gaussian Cox processes (LGCPs) 🗺️📈 - Bayesian inference with #RINLA 📊📦 - Species distribution modeling 🕸️💻 👉 paulamoraga.com/book-spatial/p… #rstats #spatial #gischat #datascience #epitwitter

Dynamic Spatial Treatment Effects as Continuous Functionals: Theory and Evidence from Healthcare Access. arxiv.org/abs/2510.15324

I shared the animated version of this map two days ago but I really like the static version too! Source: reddit.com/r/dataisbeauti…