#diffusionmodels نتائج البحث

🔥 Revolutionizing #DiffusionModels! 🔥 Unlike RL methods (e.g., Diffusion-DPO) or costly Diffusion #InferenceScaling, our Diffusion-Sharpening: ⚡ Converges faster during training ⚡ Slashes inference costs ⚡ Excels in text alignment, compositionality, and human preferences

LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences
LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences
LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences
LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences

Honored to deliver a keynote at DAGM GCPR 2025 (@gcpr_by_dagm) today, sharing our team’s recent work on fairness and controllability in GenAI. It was inspiring to engage with brilliant researchers advancing the frontiers of #ComputerVision, #DiffusionModels and #FairAI

rvbabuiisc's tweet image. Honored to deliver a keynote at DAGM GCPR 2025 (@gcpr_by_dagm) today, sharing our team’s recent work on fairness and controllability in GenAI. It was inspiring to engage with brilliant researchers advancing the frontiers of #ComputerVision, #DiffusionModels and #FairAI

Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg (@gcpr_by_dagm) on “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

val_iisc's tweet image. Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg  (@gcpr_by_dagm) on  “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

🎉 Our paper “Unlocking Dataset Distillation with Diffusion Models” has been accepted at #NeurIPS 25! We show how to unlock end-to-end dataset distillation through diffusion models by tackling the vanishing gradient problem! 📄 : arxiv.org/abs/2403.03881 #DiffusionModels


🚀 Our MatchDiffusion was accepted to ICCV 2025 in Hawaii! 🌺 We generate two synchronized videos from text prompts—designed for match-cuts. Results: matchdiffusion.github.io Paper: arxiv.org/abs/2411.18677 #MatchDiffusion #ICCV2025 #DiffusionModels #TextToVideo #GenerativeAI


🚀 Excited to share our newest paper, led by Jing Jia, on #DiffusionModels! Pair the initial Gaussian noise with its negative → two "opposite" images! 📄Paper: lnkd.in/ew7kTAiA 🌐Project: lnkd.in/eshQjSBU 📝Blog: lnkd.in/eNkaJnWJ

GuanyangW's tweet image. 🚀 Excited to share our newest paper, led by Jing Jia, on #DiffusionModels! Pair the initial Gaussian noise with its negative → two "opposite" images!
📄Paper: lnkd.in/ew7kTAiA  
🌐Project: lnkd.in/eshQjSBU 
📝Blog: lnkd.in/eNkaJnWJ

🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score! 📄 Link: arxiv.org/abs/2506.03979 (1/6) #DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo

haoxuan_steve_c's tweet image. 🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score!
📄 Link: arxiv.org/abs/2506.03979 (1/6)
#DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo
haoxuan_steve_c's tweet image. 🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score!
📄 Link: arxiv.org/abs/2506.03979 (1/6)
#DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo

👋ML Applied Researcher needed! Join M-XR in London to: - Work with diffusion & image models - Refine CLIP, SAM & DINO - Transform photography into accurate PBR materials Link bellow 👇 #MachineLearning #DiffusionModels #3D #JobOpportunity


#DiffusionModels 🎓 Our "Diffusion Models and Their Applications" course is now fully available! It includes all the lecture slides, recordings, and hands-on programming assignments. Hope it helps anyone studying diffusion models. 🌐 mhsung.github.io/kaist-cs492d-f…


Despite the remarkable empirical success of #diffusion models, their fundamental mechanisms are still poorly understood. A new article on the SIAM News blog explores important questions about the #generalizability of #DiffusionModels: siam.org/publications/s…

TheSIAMNews's tweet image. Despite the remarkable empirical success of #diffusion models, their fundamental mechanisms are still poorly understood. A new article on the SIAM News blog explores important questions about the #generalizability of #DiffusionModels: siam.org/publications/s…

Too many artifacts for GS reconstruction? Please checkout GenFusion: Closing the Loop between Reconstruction and Generation via Videos 🌐 Project page: genfusion.sibowu.com 💻 Code: github.com/Inception3D/Ge… #3D #DiffusionModels #ViewSynthesis #GenFusion #CVPR2025


🚨We’re thrilled to present our paper “CDI: Copyrighted Data Identification in #DiffusionModels” at #CVPR2025 in Nashville! 🎸❗️ "Was this diffusion model trained on my dataset?" Learn how to find out: 📍 Poster #276 🗓️ Saturday, June 14 🕒 3:00 – 5:00 PM PDT…

jan_dubinski_'s tweet image. 🚨We’re thrilled to present our paper “CDI: Copyrighted Data Identification in #DiffusionModels” at #CVPR2025 in Nashville! 🎸❗️

"Was this diffusion model trained on my dataset?"
Learn how to find out:
📍 Poster #276
🗓️ Saturday, June 14
🕒 3:00 – 5:00 PM PDT…

A team of researchers has introduced Animate Anyone, a new diffusion models-based solution for consistent and controllable image-to-video synthesis for character animation. More examples here: 80.lv/articles/check… #diffusion #diffusionmodels #ai #research #tech #technology


🚀 "Leveraging Latent #DiffusionModels for Training-Free In-Distribution Data Augmentation for Surface #DefectDetection" has been accepted to the 21st International Conference on Content-based Multimedia Indexing! 🥳 👨‍💻 Code and arXiv will be released soon.

l_capogrosso's tweet image. 🚀 "Leveraging Latent #DiffusionModels for Training-Free In-Distribution Data Augmentation for Surface #DefectDetection" has been accepted to the 21st International Conference on Content-based Multimedia Indexing! 🥳

👨‍💻 Code and arXiv will be released soon.

Check this newly published article "Ultra-Low Bitrate Predictive Portrait #VideoCompression with #DiffusionModels" at brnw.ch/21wW2pC Authors: Xinyi Chen et al. #mdpisymmetry @ComSciMath_Mdpi

Symmetry_MDPI's tweet image. Check this newly published article "Ultra-Low Bitrate Predictive Portrait #VideoCompression with #DiffusionModels" at brnw.ch/21wW2pC
Authors: Xinyi Chen et al.
#mdpisymmetry
@ComSciMath_Mdpi

🔥🚀 Our survey on diffusion-based inverse problem solvers is now live on arXiv! arxiv.org/pdf/2410.00083 #MachineLearning #DiffusionModels

The first version of our survey is now on arXiv: arxiv.org/abs/2410.00083 Many people reached out with positive and constructive feedback. Thank you! We will incorporate it in the next revision in the next few weeks.



🚀【Large Language Diffusion Models】#DiffusionModels #LLM #LLaDA We built LLaDA-8B—the FIRST non-autoregressive model rivaling LLaMA3! CRUSHES Llama2-7B on ~20 tasks while unlocking ICL/instruction-following/multi-turn chat

LiChongxuan's tweet image. 🚀【Large Language Diffusion Models】#DiffusionModels #LLM #LLaDA
We built LLaDA-8B—the FIRST non-autoregressive model rivaling LLaMA3! CRUSHES Llama2-7B on ~20 tasks while unlocking ICL/instruction-following/multi-turn chat
LiChongxuan's tweet image. 🚀【Large Language Diffusion Models】#DiffusionModels #LLM #LLaDA
We built LLaDA-8B—the FIRST non-autoregressive model rivaling LLaMA3! CRUSHES Llama2-7B on ~20 tasks while unlocking ICL/instruction-following/multi-turn chat
LiChongxuan's tweet image. 🚀【Large Language Diffusion Models】#DiffusionModels #LLM #LLaDA
We built LLaDA-8B—the FIRST non-autoregressive model rivaling LLaMA3! CRUSHES Llama2-7B on ~20 tasks while unlocking ICL/instruction-following/multi-turn chat
LiChongxuan's tweet image. 🚀【Large Language Diffusion Models】#DiffusionModels #LLM #LLaDA
We built LLaDA-8B—the FIRST non-autoregressive model rivaling LLaMA3! CRUSHES Llama2-7B on ~20 tasks while unlocking ICL/instruction-following/multi-turn chat

¡REVOLUCIÓN en Generación de Imágenes IA! Los RAEs y DiTDH destrozan récords, logrando un FID 1.13 y acelerando la convergencia 47X frente a VAEs. Olvídate del SD-VAE. El futuro es RAE. Descubre el porqué: #IA #DiffusionModels #DiTDH #RAE #SOTA youtu.be/UuHr2n6ojKs #AI #LLM


🧠 DiffusionNFT.com — inspired by cutting-edge AI research. Perfect for: 🎨 Diffusion model projects ⚙️ RL & generative AI platforms 💎 AI art or Web3 innovation A domain bridging AI and creativity. 👉 #AI #DiffusionModels #NFT #Web3 #Domains

GoAhmedBen's tweet image. 🧠 DiffusionNFT.com — inspired by cutting-edge AI research.

Perfect for:
🎨 Diffusion model projects
⚙️ RL & generative AI platforms
💎 AI art or Web3 innovation

A domain bridging AI and creativity.
👉 

#AI #DiffusionModels #NFT #Web3 #Domains

🎚️From “a hint of red” to “maximum red” ♥️ Kontinuous Kontext makes instruction-based editing truly continuous! 🌐 snap-research.github.io/kontinuouskont… #AI #DiffusionModels #GenerativeAI #SnapResearch Kudos to my coauthors! @OPatashnik @vehsatso @rvbabuiisc @DanielCohenOr1 @kcjacksonwang


MIT's Steerable Scene Generation uses diffusion AI to train robots with diverse 3D scenes. Join Amplify AI Workshop: mylnks.xyz/amplifyai #AI #Robotics #DiffusionModels


🎉 Our paper “Unlocking Dataset Distillation with Diffusion Models” has been accepted at #NeurIPS 25! We show how to unlock end-to-end dataset distillation through diffusion models by tackling the vanishing gradient problem! 📄 : arxiv.org/abs/2403.03881 #DiffusionModels


youtu.be/bmr718eZYGU?si… This is the video I've been waiting for, as far as Ai updates. I have an interest in the way #DiffusionModels work, and what she's saying confirms my beliefs that companies/coders are experiencing encountering "fog". Nothing bad - just a malaise in models

_slumberj's tweet card. Text diffusion: A new paradigm for LLMs

youtube.com

YouTube

Text diffusion: A new paradigm for LLMs


Proud to see our latest research featured! Diffusion-based text generation is opening new possibilities for fast, efficient code synthesis. 🚀 #AI #DiffusionModels #CodeGeneration

Salesforce AI Research Releases CoDA-1.7B: a Discrete-Diffusion Code Model with Bidirectional, Parallel Token Generation Salesforce AI Research released CoDA-1.7B, a discrete-diffusion code LLM that denoises masked sequences with bidirectional context and updates multiple tokens…



Our in-house text diffusion model for code generation is here — delivering massive inference speedups over traditional autoregressive models. ⚡️🚀 #AI #CodeGeneration #DiffusionModels

CoDA-1.7B: A diffusion language model for code generation with bidirectional context understanding 🔄 📄 Technical Report: bit.ly/3IBlzGG 🤗 Model: bit.ly/48dX1xN 💻 Code: bit.ly/3VSXKwT The model achieves 54.3% pass@1 on HumanEval 📊 while matching…

SFResearch's tweet image. CoDA-1.7B: A diffusion language model for code generation with bidirectional context understanding 🔄

📄 Technical Report: bit.ly/3IBlzGG
🤗 Model: bit.ly/48dX1xN
💻 Code: bit.ly/3VSXKwT

The model achieves 54.3% pass@1 on HumanEval 📊 while matching…


🚀 DC-Gen is here to supercharge text-to-image generation! By compressing the latent space without retraining, it slashes 4K image generation time by up to 138x from minutes to just 3.5s on a single GPU. High quality, ultra fast. #AI #DiffusionModels #TextToImage

jcmobarec's tweet image. 🚀 DC-Gen is here to supercharge text-to-image generation!
By compressing the latent space without retraining, it slashes 4K image generation time by up to 138x from minutes to just 3.5s on a single GPU.
High quality, ultra fast.
#AI #DiffusionModels #TextToImage

Looking forward to seeing everyone in Mexico City for hashtag#NeurIPS2025! 🇲🇽 #NeurIPS #GenerativeAI #DiffusionModels #Entropy #MachineLearning #AIResearch #SPARKE #StableDiffusion #Diversity


A 16% drop in FID for low‑resolution images – and it works with any existing diffusion model 🚀 Results are striking: • SD3.5 on LAION‑COCO improves FID by 15.89% (310.40 → 276.90) at 128×128. #AI #DiffusionModels #ComputerVision #TechInnovation #MachineLearning


It was a great honour to host @rvbabuiisc at #GCPR2025 in Freiburg. Prof. Venkatesh delivered an inspiring keynote on Towards Fair and Controllable Diffusion Models, sharing exciting recent work from @val_iisc 🚀 #AI #DiffusionModels #FairAI

Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg (@gcpr_by_dagm) on “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

val_iisc's tweet image. Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg  (@gcpr_by_dagm) on  “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI


Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg (@gcpr_by_dagm) on “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

val_iisc's tweet image. Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg  (@gcpr_by_dagm) on  “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

Honored to deliver a keynote at DAGM GCPR 2025 (@gcpr_by_dagm) today, sharing our team’s recent work on fairness and controllability in GenAI. It was inspiring to engage with brilliant researchers advancing the frontiers of #ComputerVision, #DiffusionModels and #FairAI

rvbabuiisc's tweet image. Honored to deliver a keynote at DAGM GCPR 2025 (@gcpr_by_dagm) today, sharing our team’s recent work on fairness and controllability in GenAI. It was inspiring to engage with brilliant researchers advancing the frontiers of #ComputerVision, #DiffusionModels and #FairAI

Despite the remarkable empirical success of #diffusion models, their fundamental mechanisms are still poorly understood. A new article on the SIAM News blog explores important questions about the #generalizability of #DiffusionModels: siam.org/publications/s…

TheSIAMNews's tweet image. Despite the remarkable empirical success of #diffusion models, their fundamental mechanisms are still poorly understood. A new article on the SIAM News blog explores important questions about the #generalizability of #DiffusionModels: siam.org/publications/s…

🔥 Revolutionizing #DiffusionModels! 🔥 Unlike RL methods (e.g., Diffusion-DPO) or costly Diffusion #InferenceScaling, our Diffusion-Sharpening: ⚡ Converges faster during training ⚡ Slashes inference costs ⚡ Excels in text alignment, compositionality, and human preferences

LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences
LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences
LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences
LingYang_PU's tweet image. 🔥 Revolutionizing #DiffusionModels! 🔥

Unlike RL methods (e.g., Diffusion-DPO) or costly  Diffusion #InferenceScaling, our Diffusion-Sharpening:
⚡ Converges faster during training
⚡ Slashes inference costs
⚡ Excels in text alignment, compositionality, and human preferences

🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score! 📄 Link: arxiv.org/abs/2506.03979 (1/6) #DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo

haoxuan_steve_c's tweet image. 🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score!
📄 Link: arxiv.org/abs/2506.03979 (1/6)
#DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo
haoxuan_steve_c's tweet image. 🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score!
📄 Link: arxiv.org/abs/2506.03979 (1/6)
#DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo

From RNA to Proteins! 🧬 Scientists enhance #DiffusionModels with #ReinforcementLearning algorithms to meet specific biological goals, revolutionizing how we solve complex biological problems. Discover More: cbirt.net/optimizing-dif… #Bioinformatics #Docking #ML #AI #sciencenews

CbirtDirector's tweet image. From RNA to Proteins! 🧬
Scientists enhance #DiffusionModels with #ReinforcementLearning algorithms to meet specific biological goals, revolutionizing how we solve complex biological problems.

Discover More: cbirt.net/optimizing-dif…

#Bioinformatics #Docking #ML #AI #sciencenews

Join us at #SIIM23 for @khosravi_bardia's presentation on conditional radiograph generation and learn what this video represents? #GenerativeAl #DiffusionModels Don't miss this opportunity! ⏰ June 16th, 8:00 AM CST 🏢 R9 / L3 @SIIM_Tweets

MayoAILab's tweet image. Join us at #SIIM23 for @khosravi_bardia's presentation on conditional radiograph generation and learn what this video represents? #GenerativeAl #DiffusionModels

Don't miss this opportunity! 

⏰ June 16th, 8:00 AM CST
🏢 R9 / L3

@SIIM_Tweets

Reverse Stable Diffusion: What prompt was used to generate this image? #stablediffusion #diffusionmodels

MonaJalal_'s tweet image. Reverse Stable Diffusion: What prompt was used to generate this image? #stablediffusion #diffusionmodels

Honored to deliver a keynote at DAGM GCPR 2025 (@gcpr_by_dagm) today, sharing our team’s recent work on fairness and controllability in GenAI. It was inspiring to engage with brilliant researchers advancing the frontiers of #ComputerVision, #DiffusionModels and #FairAI

rvbabuiisc's tweet image. Honored to deliver a keynote at DAGM GCPR 2025 (@gcpr_by_dagm) today, sharing our team’s recent work on fairness and controllability in GenAI. It was inspiring to engage with brilliant researchers advancing the frontiers of #ComputerVision, #DiffusionModels and #FairAI

Very proud of my students' contributions at @icmlconf! Our 7 papers cover the power of #LLMs, #DataCentricAI, #DiffusionModels, #Meta-Learning, #Reinforcement Learning & more! All in service of our #RealityCentricAIagenda! Read all about our papers here: vanderschaar-lab.com/van-der-schaar…

MihaelaVDS's tweet image. Very proud of my students' contributions at @icmlconf! Our 7 papers cover the power of #LLMs, #DataCentricAI, #DiffusionModels, #Meta-Learning, #Reinforcement Learning & more! All in service of our #RealityCentricAIagenda! Read all about our papers here: vanderschaar-lab.com/van-der-schaar…

¿Quieres conocer más sobre #DiffusionModels, capaces de crear imágenes a partir de ruido mediante #denoising y aprendizaje automático? Podrás hacerlo desde un nuevo Madrid #MachineLearning Meetup. 🗓️8/02 🔗meetup.com/madrid-machine… #somosUPM #deeplearningc @urjc @MADRID

La_UPM's tweet image. ¿Quieres conocer más sobre #DiffusionModels, capaces de crear imágenes a partir de ruido mediante #denoising y aprendizaje automático? Podrás hacerlo desde un nuevo Madrid #MachineLearning Meetup. 
🗓️8/02
🔗meetup.com/madrid-machine…
#somosUPM #deeplearningc @urjc @MADRID

A tad late to the party, but happy to share that CycleNet has been accepted to #NeurIPS2023 @NeurIPSConf! Consistency has been a pain in text-guided image editing with #DiffusionModels and here is our solution to guarantee cycle consistency...🧵[1/n] 📍cyclenetweb.github.io

ziqiao_ma's tweet image. A tad late to the party, but happy to share that CycleNet has been accepted to #NeurIPS2023 @NeurIPSConf! Consistency has been a pain in text-guided image editing with #DiffusionModels and here is our solution to guarantee cycle consistency...🧵[1/n]

📍cyclenetweb.github.io

Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models Somepalli et al.: arxiv.org/abs/2212.03860 #Artificialintelligence #Deeplearning #DiffusionModels

Montreal_AI's tweet image. Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models

Somepalli et al.: arxiv.org/abs/2212.03860

#Artificialintelligence #Deeplearning #DiffusionModels

Come chat with us today (@GrigoryBartosh and Dmitry Vetrov) about how to improve diffusion modelling during the first poster session of #ICML2024! 📜 Neural Diffusion Models ⏲️ 11:30-13:00 📍Hall C 4-9 #712 #DiffusionModels #VAEs #GenerativeAI #GenAI

canaesseth's tweet image. Come chat with us today (@GrigoryBartosh and Dmitry Vetrov) about how to improve diffusion modelling during the first poster session of #ICML2024!

📜 Neural Diffusion Models
⏲️ 11:30-13:00
📍Hall C 4-9 #712

#DiffusionModels #VAEs #GenerativeAI #GenAI
canaesseth's tweet image. Come chat with us today (@GrigoryBartosh and Dmitry Vetrov) about how to improve diffusion modelling during the first poster session of #ICML2024!

📜 Neural Diffusion Models
⏲️ 11:30-13:00
📍Hall C 4-9 #712

#DiffusionModels #VAEs #GenerativeAI #GenAI

1/5 GoodDrag: A groundbreaking study that explores good practices for drag editing with diffusion models. This research aims to enhance the user experience and empower creators in the realm of image editing. #DiffusionModels #ImageEditing

AbhinavGirdhar's tweet image. 1/5
GoodDrag: A groundbreaking study that explores good practices for drag editing with diffusion models. This research aims to enhance the user experience and empower creators in the realm of image editing. #DiffusionModels #ImageEditing

Day 258 InfiniteYou: A Leap in Identity-Preserved Image Generation! 🎨✨ Meet InfiniteYou (InfU), one of the first robust frameworks leveraging Diffusion Transformers (DiTs) like FLUX to master this task. #AI #GenerativeAI #DiffusionModels #InfiniteYou #ArtificialIntelligence

MastersNitish's tweet image. Day 258
InfiniteYou: A Leap in Identity-Preserved Image Generation! 🎨✨

Meet InfiniteYou (InfU), one of the first robust frameworks leveraging Diffusion Transformers (DiTs) like FLUX to master this task.

#AI #GenerativeAI #DiffusionModels #InfiniteYou #ArtificialIntelligence

Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg (@gcpr_by_dagm) on “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

val_iisc's tweet image. Prof. Venkatesh delivered a keynote at DAGM German Conference on Pattern Recognition, Freiburg  (@gcpr_by_dagm) on  “Towards Fair and Controllable Diffusion Models.” sharing the recent works from @val_iisc 🚀 #AI #DiffusionModels #FairAI

Stable Target Field for Reduced Variance Score Estimation in Diffusion Models Xu et al.: arxiv.org/abs/2302.00670 #Artificialintelligence #DeepLearning #DiffusionModels

Montreal_IA's tweet image. Stable Target Field for Reduced Variance Score Estimation in Diffusion Models

Xu et al.: arxiv.org/abs/2302.00670

#Artificialintelligence #DeepLearning #DiffusionModels

Stable Target Field for Reduced Variance Score Estimation in Diffusion Models Xu et al.: arxiv.org/abs/2302.00670 #Artificialintelligence #DeepLearning #DiffusionModels

Montreal_AI's tweet image. Stable Target Field for Reduced Variance Score Estimation in Diffusion Models

Xu et al.: arxiv.org/abs/2302.00670

#Artificialintelligence #DeepLearning #DiffusionModels

🔍 Join Us for a Panel Discussion at #MICCAI2023 on diffusion models for medical imaging. 🗓️ Sunday 08/10/2023 | 🕔 5:00 - 6:00 PM (GMT-7) 🔗 Details here: vios.science/tutorials/diff… 👇 Tag a colleague who shouldn’t miss this! 🚀 #DiffusionModels #MedicalImaging #HealthTech #AI

SnchzPedro_'s tweet image. 🔍 Join Us for a Panel Discussion at #MICCAI2023 on diffusion models for medical imaging.

🗓️ Sunday 08/10/2023 | 🕔 5:00 - 6:00 PM (GMT-7)

🔗 Details here: vios.science/tutorials/diff…

👇 Tag a colleague who shouldn’t miss this! 🚀

#DiffusionModels #MedicalImaging #HealthTech #AI…

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