Claire Boyer
- Missing Data Imputation using Optimal Transport
2020/02/10 by Boris Muzellec, Muzellec, Boris, Julie Josse +5 · 16 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques
- Imputation and low-rank estimation with Missing Not At Random data
2018/12/29 by Aude Sportisse, Claire Boyer, Sportisse, Aude +3 · 5 citations
Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Bayesian Inference #Tensor decomposition and applications
- An analysis of the noise schedule for score-based generative models
2024/02/07 by Stanislas Strasman, Antonio Ocello, Strasman, Stanislas +7 · 7 citations
Computer Science · Neuroscience · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Music Technology and Sound Studies #Music and Audio Processing #Neuroscience and Music Perception #Statistics Theory (math.ST)
- Optimal Transport-based Conformal Prediction
2025/01/31 by Gauthier Thurin, Thurin, Gauthier, Kimia Nadjahi +3 · 7 citations
Computer Science · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistical Methods and Inference
- Compressed sensing with structured sparsity and structured acquisition
2015/05/07 by Claire Boyer, Boyer, Claire, Jérémie Bigot +3 · 2 citations
Engineering · Medicine · #Advanced MRI Techniques and Applications #FOS: Computer and information sciences #Information Theory (cs.IT) #Microwave Imaging and Scattering Analysis #Sparse and Compressive Sensing Techniques
- An algorithm for variable density sampling with block-constrained acquisition
2013/10/16 by Claire Boyer, Boyer, Claire, Pierre Weiss +3 · 1 citation
Engineering · Medicine · #Advanced MRI Techniques and Applications #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Medical Imaging Techniques and Applications #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
- Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization
2025/02/05 by Yuhan Wu, Pierre Marion, Wu, Yu-Han +5 · 5 citations
Computer Science · Physics and Astronomy · #Neural Networks and Applications #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks
- Physics-informed kernel learning
2024/09/20 by Nathan Doumèche, Francis Bach, Doumèche, Nathan +5 · 3 citations
Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Statistics Theory (math.ST)
- Model-based Clustering with Missing Not At Random Data
2021/12/20 by Aude Sportisse, Matthieu Marbac, Sportisse, Aude +11 · 1 citation
Computer Science · #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Adapting to unknown noise level in sparse deconvolution
2016/06/15 by Claire Boyer, Yohann de Castro, Boyer, Claire +3 · 1 citation
Computer Science · Engineering · Mathematics · #Advanced Image Processing Techniques #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Information Theory (cs.IT) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Statistics Theory (math.ST)
- Minimax rate of consistency for linear models with missing values
2022/02/02 by Alexis Ayme, Claire Boyer, Ayme, Alexis +5 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
- Random features models: a way to study the success of naive imputation
2024/02/06 by Alexis Ayme, Claire Boyer, Ayme, Alexis +5 · 1 citation
Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Neural Networks and Applications #Statistics Theory (math.ST)