Ruiqi Gao @RuiqiGao
Research scientist @Google DeepMind. Generative modeling, representation learning. San Francisco Joined June 2019-
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We are looking for reviewers for the 2nd ICML SPIGM workshop (spigmworkshop2024.github.io). Welcome to register here! 👇
We are looking for reviewers for the 2nd ICML SPIGM workshop (spigmworkshop2024.github.io). Welcome to register here! 👇
We are glad to announce that the "Structured Probabilistic Inference & Generative Modeling" workshop will be held again on @icmlconf 2024, Vienna! Check the current schedule and updates on our website: spigmworkshop2024.github.io
It's always such an enjoyable experience on reading Sander's posts. 😃
It's always such an enjoyable experience on reading Sander's posts. 😃
It's still quite challenging to maintain the exact content for few step distillation of diffusion models. Very neat work to make this happen, and more (advanced deterministic sampling techniques etc.). Congrats to the team! 🥳
It's still quite challenging to maintain the exact content for few step distillation of diffusion models. Very neat work to make this happen, and more (advanced deterministic sampling techniques etc.). Congrats to the team! 🥳
Fast sampling with 'Multistep Consistency Models': We get 1.6 FID on Imagenet64 in 4 steps and scale text-to-image models, generating 256x256 images with 16 steps. Guess which row is distilled? With @emiel_hoogeboom @TimSalimans Arxiv: arxiv.org/abs/2403.06807
It has been a while but if you haven't checked it out, could be a fun reading if you're excited about flow matching by SD3 and want to understand more about the connection between that and diffusion models 😃
It has been a while but if you haven't checked it out, could be a fun reading if you're excited about flow matching by SD3 and want to understand more about the connection between that and diffusion models 😃
text-to-3d scenes that are automatically decomposed into the objects they contain, using only an image diffusion model & no other supervision: dave.ml/layoutlearning work w/ @poolio @BenMildenhall Alyosha Efros and @holynski_
Exciting!
Join us at Hall B1 in #NeurIPS2023 for an awesome diffusion panel with @robrombach @sedielem @ArashVahdat @RuiqiGao
If you want to chat about flow matching, stochastic interpolants, diffusion models and their links with OT (Schrödinger Bridge 🌉 hehe) catch me at poster #619 (Thurs 14 10:45-12:45) where I will be presenting "Diffusion Schrödinger Bridge Matching" (arxiv.org/abs/2303.16852).
Want more control over images generated by your diffusion model? Check out self-guidance at poster #605 this morning @ #NeurIPS2023 from Dave Epstein et al.! With no labels or fine-tuning, you can move + resize objects, 0-shot DreamBooth, and more: dave.ml/selfguidance/
Peanut, the diffusion cat was featured in a nice talk by @RuiqiGao at #NeurIPS2023
Diffusion circle at @NeurIPSConf: let's meet at 2:30pm on Thursday (tomorrow!) outside Hall E (Gate 10B) and then find a place to sit and have a chat. We'll do it old school and just sit on the floor somewhere. I'll share location updates live! Tell your friends! #NeurIPS2023 📢
A great turnout at the LDM tutorial, and a hard act to follow. If you are hungry for more; please come to our workshop on diffusion models this Friday in Hall B1: diffusionworkshop.github.io Submit questions to our fantastic panel of experts here docs.google.com/forms/d/e/1FAI…
A great turnout at the LDM tutorial, and a hard act to follow. If you are hungry for more; please come to our workshop on diffusion models this Friday in Hall B1: diffusionworkshop.github.io Submit questions to our fantastic panel of experts here docs.google.com/forms/d/e/1FAI… https://t.co/mgPblKphCG
Excited to announce our new work on using synthetic data for improving mathematical problem solving and code generation in LLMs! arxiv: arxiv.org/abs/2312.06585 A small amount of fine-tuning can lead to large gains (>6% on Hendrycks MATH with Palm-2)
Nuvo: Neural UV Mapping! It's super difficult to UV map/texture atlas geometry produced by 3D reconstruction and generation pipelines. Nuvo works on all kinds of "unruly" 3D representations (NeRF, DreamFusion, etc.) and enables easy appearance editing! pratulsrinivasan.github.io/nuvo 1/3
Looking forward to seeing you there and discuss diffusion models!
Looking forward to seeing you there and discuss diffusion models!
If you're at @NeurIPSConf, come check this out our demo at the @GoogleDeepMind booth on Wednesday at noon, we've got some cool stuff to share! 🎶 #NeurIPS2023
Very nice to see so much work leveraging learned priors for 3d reconstruction and generation! Tutorial: Latent Diffusion Models: Is the Generative Al Revolution Happening in Latent Space? #NeurIPS2023
The people want video LDMs (latent diffusion models). // @NeurIPSConf
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📢📢Most diffusion (and flow matching) models use handcrafted schedules for their denoising steps during sampling. We show how to optimize them in a principled manner for high-quality generation! @amsabour added quickstart guide & collab to get you started quickly (links below)!
📢📢 Align Your Steps: Optimizing Sampling Schedules in Diffusion Models research.nvidia.com/labs/toronto-a… TL;DR: We introduce a method for obtaining improved sampling schedules for diffusion models, resulting in better samples at the same computation cost. (1/5)
HF's dedication to true open source is such a blessing 🙏
Llama3 was trained on 15 trillion tokens of public data. But where can you find such datasets and recipes?? Here comes the first release of 🍷Fineweb. A high quality large scale filtered web dataset out-performing all current datasets of its scale. We trained 200+ ablation…
Llama3 was trained on 15 trillion tokens of public data. But where can you find such datasets and recipes?? Here comes the first release of 🍷Fineweb. A high quality large scale filtered web dataset out-performing all current datasets of its scale. We trained 200+ ablation…
We have just released 🍷 FineWeb: 15 trillion tokens of high quality web data. We filtered and deduplicated all CommonCrawl between 2013 and 2024. Models trained on FineWeb outperform RefinedWeb, C4, DolmaV1.6, The Pile and SlimPajama!
Introducing Meta Llama 3: the most capable openly available LLM to date. Today we’re releasing 8B & 70B models that deliver on new capabilities such as improved reasoning and set a new state-of-the-art for models of their sizes. Today's release includes the first two Llama 3…
It took my brain a while to parse what's going on in this video. We are so obsessed with "human-level" robotics that we forget it is just an artificial ceiling. Why don't we make a new species superhuman from day one? Boston Dynamics has once again reinvented itself. Gradually,…
Another Mamba-Attention hybrid that looks very strong! These two layers are complementary: Mamba is great at compressing information, and a few attention layers are enough to retrieve from the context for in-context learning.
Zyphra is pleased to announce Zamba-7B: - 7B Mamba/Attention hybrid - Competitive with Mistral-7B and Gemma-7B on only 1T fully open training tokens - Outperforms Llama-2 7B and OLMo-7B - All checkpoints across training to be released (Apache 2.0) - Achieved by 7 people, on 128…
Excited to finally release our open course on deep generative models! This material has been taught at Stanford/Cornell/UCLA since 2019. It includes 🎥 20 hours of video lectures ✨ 17 sets of slides 📖 Lecture notes Youtube: youtube.com/playlist?list=… Site:…
Announcing NeurIPS Preschool Track This year, we invite preschoolers to submit machine learning research papers.
Just finished my ECCV reviews. 2 of the 6 papers in my pile were 100% unedited and incoherent LLM output. If you let ChatGPT write your paper, and one of your reviews is a "strong reject" and a diatribe about why what you did is immoral: hi, that was me, we are not friends.
Check out RealmDreamer (realmdreamer.github.io)--our new 3D scene generation method! No multiview data required :) One of my favorites is this: "Fantasy lighthouse in the Arctic, surrounded by a world of ice and snow, shining with a mystical light under the aurora borealis."
RealmDreamer Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion We introduce RealmDreamer, a technique for generation of general forward-facing 3D scenes from text descriptions. Our technique optimizes a 3D Gaussian Splatting representation to match
Got a story to tell? You’ve got 72 hours. Together with @elevenlabsio, we’re launching our very first 72-hour FilmFAST. Join us April 12-14 for three days of prompts, voices, sound effects, and eye candy. Sign up to compete via the link in comments. We’ll announce the theme…
Updated list of diffusion model tutorial sources, from my lecture on diffusion.
I wrote a tutorial on diffusion models for undergrad and grad students. I tried my best to give intuitive explanations for complicated equations. Your feedback is much appreciated Thanks to those who suggested various reading materials to me arxiv.org/abs/2403.18103
A Mamba Primer (w/ Yair Schiff youtube.com/watch?v=dVH1dR… ) Mamba is a nice jumping off point to summarize foundational ideas in sequence modeling, parallel algorithms, continuous-time representations, and GPU aware algorithms. We try to put these together in the context of LMs.
How @_sholtodouglas got scouted by Google DeepMind: “Every night from 10 PM till 2 AM, I would do my own research. @jekbradbury saw some of my questions online and was like, ‘I thought I knew all the people in the world who were asking these questions. Who on Earth are you?’”
A good example is @_sholtodouglas at @GoogleDeepMind. He's quiet on Twitter, doesn't have any flashy first-author publications, and has only been in the field for ~1.5 years, but people in AI know he was one of the most important people behind Gemini's success
This blog post is an amazing exposition and analysis of consistency models, and how they relate to diffusion models, leading to several suggested improvements to the training procedure that look very promising. Definitely worth a read!
🚀Our latest blog post unveils the power of Consistency Models and introduces Easy Consistency Tuning (ECT), a new way to fine-tune pretrained diffusion models to consistency models. SoTA fast generative models using 1/32 training cost! 🔽 Get ready to speed up your generative…
We are glad to announce that the "Structured Probabilistic Inference & Generative Modeling" workshop will be held again on @icmlconf 2024, Vienna! Check the current schedule and updates on our website: spigmworkshop2024.github.io
Ideogram on the @Nasdaq billboard! 🔥
Information theory ftw 🙌 The most important thing in AI is not GPUs but coordination & governance. We must decentralize AI before it is too late 👊 lfg
It was great talking with @EMostaque pioneer of open source AI & founder @StabilityAI and hear him talk about his vision for open / decentralized AI powering human flourishing and how it fits with our vision for coordination accelerationism at @eigenlayer.
Jensen's energy and passion are contagious! I don't know how he can always lift everyone around him up.
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