Accueil
Équipe
Publications
Open Source
Démos
Évènements
Blog
Carrières
Nous joindre
Français
Français
English
ServiceNow
ServiceNow recherche
Tags
Diffusion models
ServiceNow recherche
Diffusion models
Unifying Autoregressive and Diffusion-Based Sequence Generation
We present significant extensions to diffusion-based sequence generation models, blurring the line with autoregressive language models. …
Nima Fathi
,
Torsten Scholak
,
Pierre-André Noël
Conference on Language Modeling (COLM), 2025.
PDF
Citation
Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion
We propose Adaptive Diffusion Denoised Smoothing, a method for certifying the predictions of a vision model against adversarial …
Frederick Shpilevskiy
,
Saiyue Lyu
,
Krishnamurthy (Dj) Dvijotham
,
Mathias Lécuyer
,
Pierre-André Noël
Workshop at the International Conference of Machine Learning (ICML), 2025.
PDF
Citation
Unifying Autoregressive and Diffusion-Based Sequence Generation
We take significant steps toward unifying autoregressive and diffusion-based sequence generation by extending the SEDD discrete …
Nima Fathi
,
Torsten Scholak
,
Pierre-André Noël
Workshop at the International Conference of Learning Representation (ICLR), 2025.
PDF
Citation
Exploring validation metrics for offline model-based optimisation with diffusion models
In model-based optimisation (MBO) we are interested in using machine learning to design candidates that maximise some measure of reward …
Christopher Beckham
,
Alexandre Piche
,
David Vazquez
,
Christopher Pal
Transactions on Machine Learning Research (TMLR), 2024.
PDF
Citation
Code
Are Diffusion Models Vision-And-Language Reasoners?
Text-conditioned image generation models have recently shown immense qualitative success using denoising diffusion processes. However, …
Benno Krojer
,
Elinor Poole-Dayan
,
Vikram Voleti
,
Christopher Pal
,
Siva Reddy
Conference on Neural Information Processing Systems (NeurIPS), 2023.
PDF
Citation
Code
Exploring the Design Space of Generative Diffusion Processes for Sparse Graphs
We extend score-based generative diffusion processes (GDPs) to sparse graphs and other inherently discrete data, with a focus on …
Pierre-André Noël
,
Pau Rodriguez
Workshop at the Neural Information Processing Systems (NeurIPS), 2022.
PDF
Citation
Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be …
Vikram Voleti
,
Alexia Jolicoeur-Martineau
,
Christopher Pal
Conference on Neural Information Processing Systems (NeurIPS), 2022.
PDF
Citation
Code
Citation
×