A new #BSSA paper led by @solvithrastar of @ETH_ERDW @SWP_ETHZurich presents REVEAL, a global-scale, transversely isotropic full-waveform inversion model that assimilates more than 6 million waveforms.
https://t.co/XNmKothXIO
Take a look at our latest Brain-Computer Interface demo, the PULP's Cerbero! Thorir @ThorirMar is driving a drone with his mind, no laptops needed, all powered by our BioGAP platform: https://t.co/U5WfosVzrb
🚨📺 NEW VIDEO 📺🚨
In our latest video, @solvithrastar presents a novel approach to global-scale full-waveform inversion (FWI) that can reduce computational cost by over an order of magnitude.
Check it out here:
https://t.co/wU3M04HWVr
#seismology#geophysics#science#fwi
📰 Brand new paper out!
Global Earth model created in record time using wavefield-adapted meshes and stochastic optimization.
It's a riveting read, comes highly recommended! 🚜
https://t.co/ZlvlpuykEk
Check out our most recent publication by @solvithrastar et al. where they present a novel approach to global-scale full-waveform inversion (FWI) that can reduce computational cost by over an order of magnitude:
https://t.co/RWadprkoxy
#fwi#seismology#geophysics
Experiments on volcanoes are still a novel use for distributed acoustic sensing, but the goal is to develop the technique into a real-time monitoring tool, write @saraklaasen, @solvithrastar, Andreas Fichtner, @yesimcubuk, and @krjonsdottir.
https://t.co/5PBQJDhEZP
For the past few years, many #fiber measurements were mere proofs of principle. But the field is now maturing, says Andreas Fichtner, a seismologist at ETH Zurich. @SWP_ETHZurich@solvithrastar@ScienceMagazine#Iceland https://t.co/23Je5oW3GZ
Earlier this year several of our group members went to Iceland to study the Grímsvötn volcano using Distributed Acoustic Sensing (DAS). In this short video you can see what they were up to on Europe's biggest ice cap.
https://t.co/N3a03I5qn5
#geophysics#iceland#earthscience
We are sharing with you our latest paper "ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network" by @ThorirMar in which we present a novel, lightweight TCN architecture for cardiac arrhythmia classification. GAP8 inside😀. https://t.co/0nn58oYSOT