Latest Updates and Announcements from Kraina Lab
We’re delighted to announce that our submission to the GeoAI workshop at SIGSPATIAL 2023 has been accepted! We’ll be presenting a paper describing our open-source library for geospatial data processing and represenation learning.
We’re delighted to announce that our submission to the UrbanAI workshop at SIGSPATIAL 2023 has been accepted! We’ll be presenting a paper describing our open-source library for geospatial data processing and represenation learning.
We’re delighted to announce that our abstract has been accepted! We’ll be an offline lightning talk at the conference. You can find more information in our publications page.
Members of Kraina AI will be presenting a comprehensive tutorial on geospatial machine learning at the ML in PL Conference 2023 in Warsaw, Poland.
We’re delighted to announce that our submission to EuroSciPy 2023 has been accepted! We’ll be presenting a tutorial on geospatial machine learning with SRAI and a poster about the SRAI project.
We’re delighted to announce that the Unite! meta university project will be financing our proposal for a PhD position on the verge of NLP and geospatial data with a focus on large language models and content generation.
Kraina AI’s team leader presented a vision talk on large models and map generation at the SDSS workshop.
We’re delighted to announce that our submission to GeoAI@SigSpatial 2022 has been accepted! We’ll be presenting a paper on OpenStreetMap region representation learning with respect to their road network characteristics.
We’re delighted to announce that our submission to the 4th ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities (ARIC) has been accepted! We’ll be presenting a paper on effective geographic transfer learning using OpenStreetMap region features for bike station location predictions.
We’re delighted to announce that our submission to GeoSearch @ SigSpatial 2021 has been accepted! We’ll be presenting a paper on OpenStreetMap region representation learning with respect to public transport quality offering.
We’re delighted to announce that our submission to SigSpatial 2021 has been accepted! We’ll be presenting a paper on OpenStreetMap region representation learning with respect to their urban and POI characteristics.
