We compare our method with the state-of-the-art on both synthetic and experimental benchmarks. Empirically, cryoSPIN outperforms in reconstruction quality and FSC.
[6/7]
🎉🎉Excited to share that “CryoSPIN” has been accepted to #NeurIPS2024!
Special thanks to my amazing collaborators and supervisors @DaveLindell, @marcusabrubaker, and @fleet_dj
Paper: https://t.co/D63rG6SWFr
Webpage: https://t.co/jcFbHoYXQm
Code is also released!
🧵[1/7]
DRaFT backpropagates the reward directly into LoRA parameters – we don’t need to use RL because diffusion sampling is differentiable. We improve efficiency by truncating the BPTT; even truncating to one step still works! (2/5)
.@clark_kev & I are excited to share our new work on studying Imagen by evaluating it as a zero-shot classifier! Highlights include Imagen achieving SoTA on Stylized Imagenet and being able to perform attribute binding in certain settings unlike CLIP
https://t.co/rGiN03qred
🧵👇
📄 An updated paper describing 3D Flexible Refinement is now out in @naturemethods!
Paper: https://t.co/sCn0nVmcEx
It describes further experimental #cryoEM results and the improved 3DFlex method that was released in #CryoSPARC v4.1 ❄️⚡
Tutorial: https://t.co/ct3QT93W2m
Thrilled to announce SR3+, our new model that establishes a new state-of-the-art on diffusion-based super-resolution for images in the wild!
https://t.co/n6KZAODjhN
Joint work w/ @watson_nn@Chitwan_Saharia@fleet_dj
We've just released the first version of our Deep Learning Tuning Playbook! This is our attempt to distill our process for actually getting good results with deep learning. We emphasize hyperparameter tuning since it has been a large pain point. https://t.co/PjeJVWeOzS
Excited to announce our work on novel view synthesis with diffusion models! Our model can lift a single 2d image into 3d.
https://t.co/z1ynTchHvE
Joint work w/ @wchan212@rmbrualla@hojonathanho@taiyasaki@mo_norouzi
Happy to announce DreamFusion, our new method for Text-to-3D!
https://t.co/4xI2VHcoQW
We optimize a NeRF from scratch using a pretrained text-to-image diffusion model. No 3D data needed!
Joint work w/ the incredible team of @BenMildenhall@ajayj_@jon_barron#dreamfusion
If you don’t think DallE-2 and Imagen are an Alexnet level moment in the machine learning world you aren’t paying attention enough. Very impressive visual results coming out of these. Getting similar chills to when I saw first web browser, iPhone, etc.
It was 16 years ago, in 2006, that @geoffreyhinton et al released their demo of deep belief nets. Undergrad me was highly impressed, and helped convince me that deep learning was the way to go. I refreshed Geoff's website almost every day checking for new papers... (1/n)