358 citations · 532 across the 23 of their papers we have counts for
23 papers
Kastor: An efficient fine-tuning strategy for generative emulation of PDE simulations
Guillaume Couairon, Alexis Jacq, Yu-Han Wu +4
Machine learning offers a promising avenue to accelerate physical simulations by replacing computationally expensive traditional Partial Differential Equation (PDE) solvers with fa…
Diffusion Fine-tuning with Rewarded Moment Matching Distillation
Alexis Jacq, Guillaume Couairon, Valentin De Bortoli +3
Distillation and Reinforcement Learning (RL) fine-tuning are the primary pillars of diffusion post-training. While traditionally studied in isolation, the interaction between these…
AsyncPatch Diffusion: spatially-flexible image generation
Samuele Papa, Valentin De Bortoli, Guillaume Couairon +3
Standard diffusion models corrupt an entire sample with a single shared noise level, forcing all spatial regions to follow the same denoising trajectory. We introduce AsyncPatch Di…
Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations
Renu Singh, Robert Brunstein, Antonia Jost +5
We evaluate the climate simulation capabilities of ArchesWeather and ArchesWeatherGen, two machine learning models originally trained for weather forecasting and evaluated up to a…
AIMIP Phase 1: systematic evaluations of AI weather and climate models
Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18
We present the AI weather and climate model intercomparison project (AIMIP), phase 1. Drawing from the rich tradition of intercomparisons in climate model development, we specify a…
ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matching
Graham Clyne, Guillaume Couairon, Guillaume Gastineau +2
Internal variability is a dominant contributor to the uncertainty of predictions at the interannual to decadal timescale. A typical approach to separating the internal variability…
ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting
Guillaume Couairon, Renu Singh, Anastase Charantonis +2
Weather forecasting plays a vital role in today's society, from agriculture and logistics to predicting the output of renewable energies, and preparing for extreme weather events.…
Large Concept Models: Language Modeling in a Sentence Representation Space
LCM team, Loïc Barrault, Paul-Ambroise Duquenne +18
LLMs have revolutionized the field of artificial intelligence and have emerged as the de-facto tool for many tasks. The current established technology of LLMs is to process input a…
ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution
Guillaume Couairon, Christian Lessig, Anastase Charantonis +1
One of the guiding principles for designing AI-based weather forecasting systems is to embed physical constraints as inductive priors in the neural network architecture. A popular…
FreeSeg-Diff: Training-Free Open-Vocabulary Segmentation with Diffusion Models
Barbara Toniella Corradini, Mustafa Shukor, Paul Couairon +3
Foundation models have exhibited unprecedented capabilities in tackling many domains and tasks. Models such as CLIP are currently widely used to bridge cross-modal representations,…
Functional Invariants to Watermark Large Transformers
Pierre Fernandez, Guillaume Couairon, Teddy Furon +1
The rapid growth of transformer-based models increases the concerns about their integrity and ownership insurance. Watermarking addresses this issue by embedding a unique identifie…
Gradpaint: Gradient-Guided Inpainting with Diffusion Models
Asya Grechka, Guillaume Couairon, Matthieu Cord
Denoising Diffusion Probabilistic Models (DDPMs) have recently achieved remarkable results in conditional and unconditional image generation. The pre-trained models can be adapted…
Zero-shot spatial layout conditioning for text-to-image diffusion models
Guillaume Couairon, Marlène Careil, Matthieu Cord +2
Large-scale text-to-image diffusion models have significantly improved the state of the art in generative image modelling and allow for an intuitive and powerful user interface to…
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards
Alexandre Ramé, Guillaume Couairon, Mustafa Shukor +4
Foundation models are first pre-trained on vast unsupervised datasets and then fine-tuned on labeled data. Reinforcement learning, notably from human feedback (RLHF), can further a…
Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar
Jamie Tolan, Hung-I Yang, Ben Nosarzewski +13
Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeated measurement…
The Stable Signature: Rooting Watermarks in Latent Diffusion Models
Pierre Fernandez, Guillaume Couairon, Hervé Jégou +2
Generative image modeling enables a wide range of applications but raises ethical concerns about responsible deployment. This paper introduces an active strategy combining image wa…
DiffEdit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk +1
Image generation has recently seen tremendous advances, with diffusion models allowing to synthesize convincing images for a large variety of text prompts. In this article, we prop…
Efficient Vision-Language Pretraining with Visual Concepts and Hierarchical Alignment
Mustafa Shukor, Guillaume Couairon, Matthieu Cord
Vision and Language Pretraining has become the prevalent approach for tackling multimodal downstream tasks. The current trend is to move towards ever larger models and pretraining…
Transformer Decoders with MultiModal Regularization for Cross-Modal Food Retrieval
Mustafa Shukor, Guillaume Couairon, Asya Grechka +1
Cross-modal image-recipe retrieval has gained significant attention in recent years. Most work focuses on improving cross-modal embeddings using unimodal encoders, that allow for e…
FlexIT: Towards Flexible Semantic Image Translation
Guillaume Couairon, Asya Grechka, Jakob Verbeek +2
Deep generative models, like GANs, have considerably improved the state of the art in image synthesis, and are able to generate near photo-realistic images in structured domains su…
FLAVA: A Foundational Language And Vision Alignment Model
Amanpreet Singh, Ronghang Hu, Vedanuj Goswami +4
State-of-the-art vision and vision-and-language models rely on large-scale visio-linguistic pretraining for obtaining good performance on a variety of downstream tasks. Generally,…
Embedding Arithmetic of Multimodal Queries for Image Retrieval
Guillaume Couairon, Matthieu Cord, Matthijs Douze +1
Latent text representations exhibit geometric regularities, such as the famous analogy: queen is to king what woman is to man. Such structured semantic relations were not demonstra…
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion
Arthur Douillard, Alexandre Ramé, Guillaume Couairon +1
Deep network architectures struggle to continually learn new tasks without forgetting the previous tasks. A recent trend indicates that dynamic architectures based on an expansion…