Today @ipam_ucla : Jamie Haddock of Harvey Mudd College - Hierarchical and neural nonnegative tensor factorizations. Watch on YouTube-> https://t.co/j620c2FYWx
Today @ipam_ucla : Kevin Kelly of Rice University Electrical and Computer Engineering - Machine Learning Enhanced Compressive Hyperspectral Imaging. Watch on YouTube-> https://t.co/RCKO98xjsh
Today @ipam_ucla : Palina Salanevich of Utrecht University - STFT Phase retrieval: robustness and generative priors. Watch on YouTube-> https://t.co/KfKvGasnYU
Today @ipam_ucla : Reinhard Heckel of the Technical University of Munich - The role of data and models for deep-learning based image reconstruction. Watch on YouTube-> https://t.co/L8He3lMKR2
Today @ipam_ucla : Mark Iwen of Michigan State University - Provably Accurate Recovery of Compactly Supported Smooth Functions from Spectrogram Measurements. Watch on YouTube-> https://t.co/kyVJheIffY
Today @ipam_ucla : Elizaveta Rebrova of Princeton University - Low-rank tensor recovery from memory-efficient measurements. Watch on YouTube-> https://t.co/lg1Of0nbSR
Today @ipam_ucla : Mary Scott of the University of California, Berkeley - Supervised and Unsupervised approaches for Electron Microscopy Data Analysis. Watch on YouTube-> https://t.co/nWNPLdI3aC
Today @ipam_ucla : Mahdi Soltanolkotabi of the University of Southern California - Medical image reconstruction via deep learning: new architectures, data reduction and robustness. Watch on YouTube-> https://t.co/r4n3B09TDx
Today @ipam_ucla : Ben Recht of the University of California, Berkeley - Splitting the difference between deep and shallow solutions of inverse problems. Watch on YouTube-> https://t.co/oHAxMPFfuT
New from @ipam_ucla : Juan-Carlos Idrobo of the University of Washington - Into the Realms of Quantum Phenomena with Electron Microscopy: Exploring New Possibilities & Limitations. Watch on YouTube-> https://t.co/P2nNiOAHJz
Today @ipam_ucla : Sarah Haigh of the University of Manchester - Probing atomic behaviour in liquids with STEM: opportunities for machine learning. Watch on YouTube-> https://t.co/fYwb7rTLXv
Today @ipam_ucla : Robert Wolkow of the University of Alberta - Atom-Defined Devices, Ultra-Fast, Ultra-Low Power Classical Devices and Diverse Quantum Devices. Watch on YouTube-> https://t.co/lpxr0mYsUV
Today @ipam_ucla : Piotr Indyk of the Massachusetts Institute of Technology - Learning-Based Low-Rank Approximations. Watch on YouTube-> https://t.co/JWPhQ3W5mz
Today @ipam_ucla : Rama Vasudevan of Oak Ridge National Laboratory - Advancing Microscopy with Machine Learning: Lessons and Insights from Scanning Probe Microscopy. Watch on YouTube-> https://t.co/uwqcofjlk8
Today @ipam_ucla : Daniel Cremers of Technische Universtitat München - Deep Learning: Challenges and Perspectives. Watch on YouTube-> https://t.co/4J6Swq3agy
I had the immense pleasure of working with the amazing team at @Slate, including @susanematthews and @DerekLJohn on the special episodes for this feature, including the episode on how they made this show. What an incredible dive into the origins of this situation in America.🔥
Today @ipam_ucla : Michael Lustig of the University of California, Berkeley - Multi-modal Motion Imaging using Microwave tones in an MRI scanner. Watch on YouTube-> https://t.co/1k4HAiVFCg
Today @ipam_ucla : Hanbaek Lyu of the University of Wisconsin-Madison - Mesoscale reconstruction of images and networks using tensor decomposition. Watch on YouTube-> https://t.co/2hJa0E3Qwr