Novel quantum generative model framework based on solving stochastic differential equations. Convex training landscape with efficient parameter recovery, enabling quantum model discovery for high-dimensional correlated data.
#QuantumML #GenerativeModels #Research
#QuantumML #GenerativeModels #Research
Quantum Fokker-Planck Solvers as Trainable Generative Models
arxiv.org
October 23, 2026 at 4:45 AM
Novel quantum generative model framework based on solving stochastic differential equations. Convex training landscape with efficient parameter recovery, enabling quantum model discovery for high-dimensional correlated data.
#QuantumML #GenerativeModels #Research
#QuantumML #GenerativeModels #Research
New arXiv work shows rectified flow models can achieve ~Õ(ε⁻²) sample complexity, improving on prior ε⁻⁴ bounds for flow matching and matching the optimal rate for mean estimation. The gains come from rectified flows’…
#AI #MachineLearning #GenerativeModels #ArXiv
https://arxiv.org/abs/2601.20250
#AI #MachineLearning #GenerativeModels #ArXiv
https://arxiv.org/abs/2601.20250
October 8, 2026 at 6:01 PM
New arXiv work shows rectified flow models can achieve ~Õ(ε⁻²) sample complexity, improving on prior ε⁻⁴ bounds for flow matching and matching the optimal rate for mean estimation. The gains come from rectified flows’…
#AI #MachineLearning #GenerativeModels #ArXiv
https://arxiv.org/abs/2601.20250
#AI #MachineLearning #GenerativeModels #ArXiv
https://arxiv.org/abs/2601.20250
Appleが発表した「Normalizing Trajectory Models (NTM)」：確率的軌跡モデリングの限界を突破する高効率生成AIアーキテクチャ
Appleが発表したNormalizing Trajectory Models (NTM)の技術解説。正確な尤度を維持しつつ数ステップでの高速生成を実現。
#GenerativeModels #NormalizingFlows #DiffusionModels #ComputerVision #MachineLearning
Appleが発表したNormalizing Trajectory Models (NTM)の技術解説。正確な尤度を維持しつつ数ステップでの高速生成を実現。
#GenerativeModels #NormalizingFlows #DiffusionModels #ComputerVision #MachineLearning
Appleが発表した「Normalizing Trajectory Models (NTM)」：確率的軌跡モデリングの限界を突破する高効率生成AIアーキテクチャ
Appleが発表したNormalizing Trajectory Models (NTM)の技術解説。正確な尤度を維持しつつ数ステップでの高速生成を実現。
ai.warp-studio.com
October 8, 2026 at 5:11 PM
Appleが発表した「Normalizing Trajectory Models (NTM)」：確率的軌跡モデリングの限界を突破する高効率生成AIアーキテクチャ
Appleが発表したNormalizing Trajectory Models (NTM)の技術解説。正確な尤度を維持しつつ数ステップでの高速生成を実現。
#GenerativeModels #NormalizingFlows #DiffusionModels #ComputerVision #MachineLearning
Appleが発表したNormalizing Trajectory Models (NTM)の技術解説。正確な尤度を維持しつつ数ステップでの高速生成を実現。
#GenerativeModels #NormalizingFlows #DiffusionModels #ComputerVision #MachineLearning
New arXiv notes frame control as dynamically constrained sampling, extending flow matching and diffusion methods to trajectory planning and steering systems toward target states. Aimed at control theory and robotics…
#Robotics #ControlSystems #GenerativeModels #AI
https://arxiv.org/abs/2609.33164
#Robotics #ControlSystems #GenerativeModels #AI
https://arxiv.org/abs/2609.33164
October 1, 2026 at 12:01 AM
New arXiv notes frame control as dynamically constrained sampling, extending flow matching and diffusion methods to trajectory planning and steering systems toward target states. Aimed at control theory and robotics…
#Robotics #ControlSystems #GenerativeModels #AI
https://arxiv.org/abs/2609.33164
#Robotics #ControlSystems #GenerativeModels #AI
https://arxiv.org/abs/2609.33164
His talk "Fail Better? The Computational Study of Character Types in Narratives" led into a lively discussion on the benefits and pitfalls of automating the #CLS annotation process with #GenerativeModels, and on how to #validate that the output we receive is actually what we were asking for.
Fail Better? The Computational Study of Character Types in Narratives
Sep 9, 2026, 12:10 pm - Fotis Jannidis is a professor of computer philology and history of contemporary German literature in the Institute for German Philology at the University of Würzburg, Germany.
www.ischool.berkeley.edu
September 14, 2026 at 12:14 AM
His talk "Fail Better? The Computational Study of Character Types in Narratives" led into a lively discussion on the benefits and pitfalls of automating the #CLS annotation process with #GenerativeModels, and on how to #validate that the output we receive is actually what we were asking for.
Explaining grounding #Grounding #GenerativeModels #ArtificialIntelligence #MachineLearning #DataScience
Explaining grounding
Grounding ties a generative model's answer to retrieved source documents: how the request flow works, who sells it, what it costs and where it still fails.
ppc.land
September 5, 2026 at 1:05 PM
Explaining grounding #Grounding #GenerativeModels #ArtificialIntelligence #MachineLearning #DataScience
Explaining grounding #Grounding #GenerativeModels #ArtificialIntelligence #MachineLearning #DataScience
Explaining grounding
Grounding ties a generative model's answer to retrieved source documents: how the request flow works, who sells it, what it costs and where it still fails.
ppc.land
September 5, 2026 at 1:05 PM
Explaining grounding #Grounding #GenerativeModels #ArtificialIntelligence #MachineLearning #DataScience
🔥 Marionette Decouples World State from Appearance for Stable Game Simulation
https://pneumetron.com/news/ai_research/marionette-decouples-world-state-from-appearance-8b2e45
#AI #ComputerVision #GameDevelopment #GenerativeModels
https://pneumetron.com/news/ai_research/marionette-decouples-world-state-from-appearance-8b2e45
#AI #ComputerVision #GameDevelopment #GenerativeModels
August 18, 2026 at 8:47 AM
🔥 Marionette Decouples World State from Appearance for Stable Game Simulation
https://pneumetron.com/news/ai_research/marionette-decouples-world-state-from-appearance-8b2e45
#AI #ComputerVision #GameDevelopment #GenerativeModels
https://pneumetron.com/news/ai_research/marionette-decouples-world-state-from-appearance-8b2e45
#AI #ComputerVision #GameDevelopment #GenerativeModels
🤖 Beyond Single-Image Tasks: CPI-Bench Aims to Standardize Real-World Image Editing Evaluation
https://pneumetron.com/news/ai_research/cpi-bench-real-world-image-editing-benchmark-5046a6
#AI #ComputerVision #GenerativeModels #Benchmarking
https://pneumetron.com/news/ai_research/cpi-bench-real-world-image-editing-benchmark-5046a6
#AI #ComputerVision #GenerativeModels #Benchmarking
August 18, 2026 at 8:47 AM
🤖 Beyond Single-Image Tasks: CPI-Bench Aims to Standardize Real-World Image Editing Evaluation
https://pneumetron.com/news/ai_research/cpi-bench-real-world-image-editing-benchmark-5046a6
#AI #ComputerVision #GenerativeModels #Benchmarking
https://pneumetron.com/news/ai_research/cpi-bench-real-world-image-editing-benchmark-5046a6
#AI #ComputerVision #GenerativeModels #Benchmarking
Are you interested in Invertible Convolution or Flow models?
I will be presenting our work 'Inverse-Flow' at #AISTATS25
Session 3, 5th may, 3-6 pm, Hall A-E 48.
#GenerativeModels , #ML, #phuket
I will be presenting our work 'Inverse-Flow' at #AISTATS25
Session 3, 5th may, 3-6 pm, Hall A-E 48.
#GenerativeModels , #ML, #phuket
May 2, 2025 at 10:43 PM
Are you interested in Invertible Convolution or Flow models?
I will be presenting our work 'Inverse-Flow' at #AISTATS25
Session 3, 5th may, 3-6 pm, Hall A-E 48.
#GenerativeModels , #ML, #phuket
I will be presenting our work 'Inverse-Flow' at #AISTATS25
Session 3, 5th may, 3-6 pm, Hall A-E 48.
#GenerativeModels , #ML, #phuket
Check out these two great courses on Diffusion and Flow models! 📚🌀
1. www.youtube.com/watch?v=8mxC...
2. www.youtube.com/watch?v=GCoP...
#GenerativeModels, #Diffusion, #Flow, #GenAI, #MachineLearning, #CompterVision, #ML
1. www.youtube.com/watch?v=8mxC...
2. www.youtube.com/watch?v=GCoP...
#GenerativeModels, #Diffusion, #Flow, #GenAI, #MachineLearning, #CompterVision, #ML
April 3, 2025 at 11:28 AM
Check out these two great courses on Diffusion and Flow models! 📚🌀
1. www.youtube.com/watch?v=8mxC...
2. www.youtube.com/watch?v=GCoP...
#GenerativeModels, #Diffusion, #Flow, #GenAI, #MachineLearning, #CompterVision, #ML
1. www.youtube.com/watch?v=8mxC...
2. www.youtube.com/watch?v=GCoP...
#GenerativeModels, #Diffusion, #Flow, #GenAI, #MachineLearning, #CompterVision, #ML
Exploring the intersection of Diffusion and Flow Matching models! 🚀 1. Flow models intro. 2. Clears up the confusion, showing how Gaussian flow matching and diffusion models align:
1. 🔗 mlg.eng.cam.ac.uk/blog/2024/01...
2. 🔗 diffusionflow.github.io
#FlowMatching #DiffusionModels #GenerativeModels
1. 🔗 mlg.eng.cam.ac.uk/blog/2024/01...
2. 🔗 diffusionflow.github.io
#FlowMatching #DiffusionModels #GenerativeModels
March 21, 2025 at 11:19 AM
Exploring the intersection of Diffusion and Flow Matching models! 🚀 1. Flow models intro. 2. Clears up the confusion, showing how Gaussian flow matching and diffusion models align:
1. 🔗 mlg.eng.cam.ac.uk/blog/2024/01...
2. 🔗 diffusionflow.github.io
#FlowMatching #DiffusionModels #GenerativeModels
1. 🔗 mlg.eng.cam.ac.uk/blog/2024/01...
2. 🔗 diffusionflow.github.io
#FlowMatching #DiffusionModels #GenerativeModels
#Fanvue #Creators using #aimodel, what applications did you use to create your models?
#aicreators #generativemodels #generativecreators
#aicreators #generativemodels #generativecreators
November 17, 2025 at 5:08 PM
#Fanvue #Creators using #aimodel, what applications did you use to create your models?
#aicreators #generativemodels #generativecreators
#aicreators #generativemodels #generativecreators
"In this exploration, I have come to understand why one would use #GenerativeModels to accomplish a specific goal, and how they can be successful in doing so. I don't think condemning people for using them is that helpful to anyone, or to whatever cause you're fighting for so fervently that […]
Original post on hachyderm.io
hachyderm.io
April 7, 2026 at 12:46 AM
"In this exploration, I have come to understand why one would use #GenerativeModels to accomplish a specific goal, and how they can be successful in doing so. I don't think condemning people for using them is that helpful to anyone, or to whatever cause you're fighting for so fervently that […]
𝐔𝐧𝐢𝐟𝐢𝐜𝐚𝐳𝐢𝐨𝐧𝐞, 𝐟𝐥𝐞𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐚̀ 𝐞 𝐯𝐢𝐬𝐢𝐨𝐧𝐞 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜𝐚: 𝐢𝐥 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠-𝐅𝐫𝐞𝐞 𝐆𝐮𝐢𝐝𝐚𝐧𝐜𝐞 (𝐓𝐅𝐆) 𝐞 𝐢𝐥 𝐟𝐮𝐭𝐮𝐫𝐨 𝐝𝐞𝐥𝐥𝐚 𝐠𝐞𝐧𝐞𝐫𝐚𝐳𝐢𝐨𝐧𝐞 𝐜𝐨𝐧𝐝𝐢𝐳𝐢𝐨𝐧𝐚𝐭𝐚
#GenerativeModels #Innovation #ArtificialIntelligence #AiGenerated #TFG
www.andreaviliotti.it/post/unifica...
#GenerativeModels #Innovation #ArtificialIntelligence #AiGenerated #TFG
www.andreaviliotti.it/post/unifica...
Unificazione ed efficienza: Il Training-Free Guidance (TFG) nei Modelli Generativi
Il Training-Free Guidance (TFG) semplifica la generazione condizionale eliminando il riaddestramento. Utilizzando predictor preaddestrati, come classificatori o funzioni di perdita, guida il processo senza sacrificare qualità. Unifica tecniche esistenti, ottimizza iperparametri ed è applicabile in contesti vari, dalle immagini alle molecole e all'audio. Mitiga bias nei dataset, riduce costi e tempi, e favorisce applicazioni scalabili, flessibili e inclusive.
www.andreaviliotti.it
December 6, 2024 at 9:55 AM
𝐔𝐧𝐢𝐟𝐢𝐜𝐚𝐳𝐢𝐨𝐧𝐞, 𝐟𝐥𝐞𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐚̀ 𝐞 𝐯𝐢𝐬𝐢𝐨𝐧𝐞 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜𝐚: 𝐢𝐥 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠-𝐅𝐫𝐞𝐞 𝐆𝐮𝐢𝐝𝐚𝐧𝐜𝐞 (𝐓𝐅𝐆) 𝐞 𝐢𝐥 𝐟𝐮𝐭𝐮𝐫𝐨 𝐝𝐞𝐥𝐥𝐚 𝐠𝐞𝐧𝐞𝐫𝐚𝐳𝐢𝐨𝐧𝐞 𝐜𝐨𝐧𝐝𝐢𝐳𝐢𝐨𝐧𝐚𝐭𝐚
#GenerativeModels #Innovation #ArtificialIntelligence #AiGenerated #TFG
www.andreaviliotti.it/post/unifica...
#GenerativeModels #Innovation #ArtificialIntelligence #AiGenerated #TFG
www.andreaviliotti.it/post/unifica...
🔍🧠 Their experiments show that #LLMs can produce reasonable poem descriptions, but struggle with more abstract interpretion, highlighting where #NLG currently meets its #limits in #LiteraryInterpretation.
#LiteraryComputing #Evaluation #GenerativeModels
#LiteraryComputing #Evaluation #GenerativeModels
January 14, 2026 at 10:31 PM
🔍🧠 Their experiments show that #LLMs can produce reasonable poem descriptions, but struggle with more abstract interpretion, highlighting where #NLG currently meets its #limits in #LiteraryInterpretation.
#LiteraryComputing #Evaluation #GenerativeModels
#LiteraryComputing #Evaluation #GenerativeModels
New article!
Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks
👉 https://cup.org/4ugXdUr
✍️Shivam Singh, Simon Michael Papalexiou, Hebatallah M. Abdelmoaty,
@tomhartvigsen.bsky.social & Antonios Mamalakis
#data #generativemodels #precipitation
Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks
👉 https://cup.org/4ugXdUr
✍️Shivam Singh, Simon Michael Papalexiou, Hebatallah M. Abdelmoaty,
@tomhartvigsen.bsky.social & Antonios Mamalakis
#data #generativemodels #precipitation
June 5, 2026 at 10:02 AM
New article!
Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks
👉 https://cup.org/4ugXdUr
✍️Shivam Singh, Simon Michael Papalexiou, Hebatallah M. Abdelmoaty,
@tomhartvigsen.bsky.social & Antonios Mamalakis
#data #generativemodels #precipitation
Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks
👉 https://cup.org/4ugXdUr
✍️Shivam Singh, Simon Michael Papalexiou, Hebatallah M. Abdelmoaty,
@tomhartvigsen.bsky.social & Antonios Mamalakis
#data #generativemodels #precipitation
🚀 Tomorrow! Prof. Joel P. Arrais (Univ. of Coimbra) on how #AI & #GenerativeModels transform drug discovery—from genomics to molecule design. Join the online #SanoSeminar 👉
sano.science/seminars/generative-models-for-drug-discovery-from-pharmacogenomics-to-targeted-molecular-design/ #DrugDiscovery
sano.science/seminars/generative-models-for-drug-discovery-from-pharmacogenomics-to-targeted-molecular-design/ #DrugDiscovery
February 3, 2026 at 10:44 AM
🚀 Tomorrow! Prof. Joel P. Arrais (Univ. of Coimbra) on how #AI & #GenerativeModels transform drug discovery—from genomics to molecule design. Join the online #SanoSeminar 👉
sano.science/seminars/generative-models-for-drug-discovery-from-pharmacogenomics-to-targeted-molecular-design/ #DrugDiscovery
sano.science/seminars/generative-models-for-drug-discovery-from-pharmacogenomics-to-targeted-molecular-design/ #DrugDiscovery
The HackerNoon Newsletter: AI Brawl: the Generative Model Showdown (11/9/2025) #Technology #EmergingTechnologies #ArtificialIntelligence #AI #GenerativeModels #TechnologyNews
The HackerNoon Newsletter: AI Brawl: the Generative Model Showdown (11/9/2025)
How are you, hacker? 🪐 What’s happening in tech today, November 9, 2025? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, The chemical element Darmstadtium...
puretech.news
November 9, 2025 at 11:27 PM
The HackerNoon Newsletter: AI Brawl: the Generative Model Showdown (11/9/2025) #Technology #EmergingTechnologies #ArtificialIntelligence #AI #GenerativeModels #TechnologyNews
A study compares cognitive architectures and generative models, noting cognitive systems favor interpretability while generative models excel in flexibility. https://getnews.me/qualitative-comparison-of-cognitive-and-generative-ai-theories/ #cognitivearchitectures #generativemodels #ai
October 7, 2025 at 2:29 PM
A study compares cognitive architectures and generative models, noting cognitive systems favor interpretability while generative models excel in flexibility. https://getnews.me/qualitative-comparison-of-cognitive-and-generative-ai-theories/ #cognitivearchitectures #generativemodels #ai
CGI lets users upload example images and correctly identifies the right generative AI model 92% of the time with just four images in a benchmark of 65 models. Read more: https://getnews.me/conditional-generative-model-identification-improves-search-via-images/ #cgimethod #generativemodels
October 1, 2025 at 10:04 AM
CGI lets users upload example images and correctly identifies the right generative AI model 92% of the time with just four images in a benchmark of 65 models. Read more: https://getnews.me/conditional-generative-model-identification-improves-search-via-images/ #cgimethod #generativemodels
Researchers prove Discrete Flow Matching models converge to true data distribution, tying total variation error to learned velocity field risk (Sep 26, 2025). Read more: https://getnews.me/theoretical-insights-into-discrete-flow-matching-generative-models/ #discreteflowmatching #generativemodels
September 29, 2025 at 4:50 PM
Researchers prove Discrete Flow Matching models converge to true data distribution, tying total variation error to learned velocity field risk (Sep 26, 2025). Read more: https://getnews.me/theoretical-insights-into-discrete-flow-matching-generative-models/ #discreteflowmatching #generativemodels
Deterministic models exactly reproduce training samples; stochastic version adds Gaussian noise to create perturbed copies, balancing memorization and variation on limited data. https://getnews.me/stochastic-interpolation-shows-generative-model-limits-with-small-data/ #generativemodels #ai
September 29, 2025 at 10:08 AM
Deterministic models exactly reproduce training samples; stochastic version adds Gaussian noise to create perturbed copies, balancing memorization and variation on limited data. https://getnews.me/stochastic-interpolation-shows-generative-model-limits-with-small-data/ #generativemodels #ai
DS‑Diffusion reduces predictive score by 5.56% and discriminative score by 61.55% versus ImagenTime, while eliminating conditional retraining. Read more: https://getnews.me/ds-diffusion-introduces-style-guided-generation-for-time-series-data/ #dsdiffusion #timeseries #generativemodels
September 27, 2025 at 5:28 AM
DS‑Diffusion reduces predictive score by 5.56% and discriminative score by 61.55% versus ImagenTime, while eliminating conditional retraining. Read more: https://getnews.me/ds-diffusion-introduces-style-guided-generation-for-time-series-data/ #dsdiffusion #timeseries #generativemodels