Fukumizu, Kenji
- Hilbert space embeddings and metrics on probability measures
2009/07/30 by Bharath K. Sriperumbudur, Arthur Gretton, Sriperumbudur, Bharath K. +7 · 33 citations
Computer Science · Medicine · #Advanced Neuroimaging Techniques and Applications #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Topological and Geometric Data Analysis
- Universality, Characteristic Kernels and RKHS Embedding of Measures
2010/03/03 by Bharath K. Sriperumbudur, Sriperumbudur, Bharath K., Kenji Fukumizu +3 · 23 citations
Mathematics · Engineering · Computer Science · #Statistical Methods and Inference #Control Systems and Identification #Bayesian Methods and Mixture Models
- On integral probability metrics, ϕ-divergences and binary classification
2009/01/18 by Bharath K. Sriperumbudur, Sriperumbudur, Bharath K., Kenji Fukumizu +7 · 14 citations
Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Fuzzy Systems and Optimization #Information Theory (cs.IT) #Statistical Mechanics and Entropy
- Density Estimation in Infinite Dimensional Exponential Families
2013/12/12 by Bharath K. Sriperumbudur, Sriperumbudur, Bharath, Kenji Fukumizu +7 · 8 citations
Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models #Statistical Methods and Inference
- Persistence weighted Gaussian kernel for topological data analysis
2016/01/08 by Genki Kusano, Kusano, Genki, Kenji Fukumizu +3 · 7 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · #Advanced Neuroimaging Techniques and Applications #Algebraic Topology (math.AT) #Cell Image Analysis Techniques #FOS: Mathematics #Topological and Geometric Data Analysis
- Learning from Distributions via Support Measure Machines
2012/02/29 by Krikamol Muandet, Kenji Fukumizu, Muandet, Krikamol +5 · 5 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Kernel Bayes' rule
2010/09/29 by Fukumizu, Kenji, Song, Le, Gretton, Arthur · 3 citations
#62F15 #62G05 #FOS: Computer and information sciences #Machine Learning (stat.ML)
- Semi-flat minima and saddle points by embedding neural networks to\n overparameterization
2019/06/11 by Kenji Fukumizu, Shoichiro Yamaguchi, Fukumizu, Kenji +5 · 4 citations
Computer Science · Engineering · Physics and Astronomy · #Advanced Measurement and Metrology Techniques #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications
- Smoothness and Stability in GANs
2020/02/11 by Casey Chu, Chu, Casey, Kentaro Minami +3 · 6 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Adversarial Robustness in Machine Learning #Generative Adversarial Networks and Image Synthesis
- Kernel method for persistence diagrams via kernel embedding and weight factor
2017/06/12 by Genki Kusano, Kenji Fukumizu, Kusano, Genki +3 · 3 citations
Computer Science · Medicine · Physics and Astronomy · #Advanced Neuroimaging Techniques and Applications #Algebraic Topology (math.AT) #Complex Network Analysis Techniques #Data Analysis #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (stat.ML) #Statistics and Probability (physics.data-an) #Topological and Geometric Data Analysis
- Deep Neural Networks Learn Non-Smooth Functions Effectively
2018/02/13 by Masaaki Imaizumi, Imaizumi, Masaaki, Kenji Fukumizu +1 · 3 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Neural Networks and Applications
- Flow matching achieves almost minimax optimal convergence
2024/05/31 by Kenji Fukumizu, Taiji Suzuki, Fukumizu, Kenji +7 · 6 citations
Engineering · Computer Science · #Advanced Control Systems Optimization #Reinforcement Learning in Robotics
- Variational Learning on Aggregate Outputs with Gaussian Processes
2018/05/22 by Ho Chung Leon Law, Law, Ho Chung Leon, Dino Sejdinović +11 · 3 citations
Computer Science · #Applications (stat.AP) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Methodology (stat.ME)
- Kernel Mean Shrinkage Estimators
2014/05/21 by Krikamol Muandet, Bharath K. Sriperumbudur, Muandet, Krikamol +7 · 2 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Statistical Methods and Inference #Gaussian Processes and Bayesian Inference
- Convergence guarantees for kernel-based quadrature rules in misspecified settings
2016/05/24 by Kanagawa, Motonobu, Sriperumbudur, Bharath K., Fukumizu, Kenji · 2 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Trimmed Density Ratio Estimation
2017/03/09 by Liu, Song, Takeda, Akiko, Suzuki, Taiji +1 · 2 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- A Linear-Time Kernel Goodness-of-Fit Test
2017/05/22 by Jitkrittum, Wittawat, Xu, Wenkai, Szabo, Zoltan +2 · 2 citations
#46E22 #62G10 #FOS: Computer and information sciences #G.3 #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings
2017/09/01 by Motonobu Kanagawa, Kanagawa, Motonobu, Bharath K. Sriperumbudur +3 · 2 citations
Decision Sciences · Engineering · Mathematics · #46E22 (Secondary) #46E35 #65D05 #65D30 (Primary) #65D32 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Mathematical Approximation and Integration #Nuclear reactor physics and engineering #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design
- Tree-Sliced Variants of Wasserstein Distances
2019/02/01 by Tam Le, Makoto Yamada, Le, Tam +5 · 2 citations
Engineering · Environmental Science · #3D Shape Modeling and Analysis #Asphalt Pavement Performance Evaluation #FOS: Computer and information sciences #Groundwater flow and contamination studies #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Unsupervised Learning of Equivariant Structure from Sequences
2022/10/12 by Miyato, Takeru, Koyama, Masanori, Fukumizu, Kenji · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Hypothesis testing using pairwise distances and associated kernels (with Appendix)
2012/05/02 by Sejdinovic, Dino, Gretton, Arthur, Sriperumbudur, Bharath +1 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
- Support Consistency of Direct Sparse-Change Learning in Markov Networks
2014/07/02 by Liu, Song, Suzuki, Taiji, Relator, Raissa +3 · 1 citation
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models
2014/09/18 by Yu Nishiyama, Motonobu Kanagawa, Nishiyama, Yu +5 · 1 citation
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms #Methodology (stat.ME)
- Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network
2023/04/25 by Kinoshita, Yuri, Oono, Kenta, Fukumizu, Kenji +2 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Learning Sparse Structural Changes in High-dimensional Markov Networks: A Review on Methodologies and Theories
2017/01/06 by Liu, Song, Fukumizu, Kenji, Suzuki, Taiji · 1 citation
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Influence Function and Robust Variant of Kernel Canonical Correlation Analysis
2017/05/09 by Md Ashad Alam, Alam, Md. Ashad, Kenji Fukumizu +3 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #FOS: Computer and information sciences #Face and Expression Recognition #Genetic and phenotypic traits in livestock #Machine Learning (stat.ML) #Statistical Methods and Inference
- Meta Learning for Causal Direction
2020/07/06 by Ton, Jean-Francois, Sejdinovic, Dino, Fukumizu, Kenji · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces
2020/11/04 by Masaaki Imaizumi, Imaizumi, Masaaki, Kenji Fukumizu +1 · 1 citation
Computer Science · Materials Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning in Materials Science
- β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap
2021/10/11 by Wu, Pengzhou, Fukumizu, Kenji · 1 citation
#Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
- Compositional simulation-based inference for time series
2024/11/05 by Manuel Gloeckler, Shoji Toyota, Gloeckler, Manuel +5 · 1 voice · 2 citations
Computer Science · #Geochemistry and Geologic Mapping
- Towards Principled Causal Effect Estimation by Deep Identifiable Models
2021/09/30 by Wu, Pengzhou, Fukumizu, Kenji · 1 citation
#Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
- A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective?
2021/08/25 by Mikami, Hiroaki, Fukumizu, Kenji, Murai, Shogo +5 · 1 citation
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Hilbert Space Embeddings of POMDPs
2012/10/16 by Yu Nishiyama, Abdeslam Boularias, Nishiyama, Yu +5 · 1 citation
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Network Security and Intrusion Detection #Water Systems and Optimization
- Procedure to Reveal the Mechanism of Pattern Formation Process by Topological Data Analysis
2022/04/26 by Mototake, Yoh-ichi, Mizumaki, Masaichiro, Kudo, Kazue +1 · 1 citation
#Data Analysis #FOS: Physical sciences #Pattern Formation and Solitons (nlin.PS) #Statistics and Probability (physics.data-an) #Strongly Correlated Electrons (cond-mat.str-el)
- Neural Fourier Transform: A General Approach to Equivariant Representation Learning
2023/05/29 by Masanori Koyama, Koyama, Masanori, Kenji Fukumizu +5 · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Morphological variations and asymmetry #Neural Networks and Applications #Statistical Mechanics and Entropy
- Extended Flow Matching: a Method of Conditional Generation with Generalized Continuity Equation
2024/02/29 by Isobe, Noboru, Koyama, Masanori, Zhang, Jinzhe +2 · 1 citation
#49Q22 (Secondary) #68T07 (Primary) #Analysis of PDEs (math.AP) #FOS: Computer and information sciences #FOS: Mathematics #Functional Analysis (math.FA) #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Probability (math.PR)
- DoubleGen: Debiased Generative Modeling of Counterfactuals
2025/09/20 by Alex Luedtke, Luedtke, Alex, Kenji Fukumizu +1 · 1 voice · 2 citations
Business, Management and Accounting · Computer Science · Physics and Astronomy · #Artificial Intelligence in Games #Business Process Modeling and Analysis #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Opinion Dynamics and Social Influence
- Scaling Law of Sim2Real Transfer Learning in Expanding Computational Materials Databases for Real-World Predictions
2024/08/07 by Shunya Minami, Yasuhiko Hayashi, Minami, Shunya +15 · 1 citation
Materials Science · #Machine Learning in Materials Science
- Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
2021/01/17 by Pengzhou Wu, Kenji Fukumizu, Wu, Pengzhou +1 · 1 citation
Computer Science · Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Methodology (stat.ME) #Statistical Methods and Inference