Muandet, Krikamol
- Domain Generalization via Invariant Feature Representation
2013/01/10 by Krikamol Muandet, Muandet, Krikamol, David Balduzzi +2 · 64 citations
Computer Science · Biochemistry, Genetics and Molecular Biology · #Domain Adaptation and Few-Shot Learning #Cancer-related molecular mechanisms research #Machine Learning and ELM
- A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
2020/02/10 by Park, Junhyung, Muandet, Krikamol · 15 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Grasping Field: Learning Implicit Representations for Human Grasps
2020/08/10 by Korrawe Karunratanakul, Karunratanakul, Korrawe, Jinlong Yang +8 · 13 citations
Engineering · Computer Science · #Robot Manipulation and Learning #Human Motion and Animation #Human Pose and Action Recognition
- Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment\n Restriction
2021/05/10 by Afsaneh Mastouri, Mastouri, Afsaneh, Yuchen Zhu +13 · 8 citations
Mathematics · #Advanced Causal Inference Techniques #Statistical Methods and Inference
- Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
2021/02/16 by Park, Junhyung, Shalit, Uri, Schölkopf, Bernhard +1 · 6 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Counterfactual Mean Embeddings
2018/05/22 by Krikamol Muandet, Muandet, Krikamol, Motonobu Kanagawa +5 · 4 citations
Mathematics · #Advanced Causal Inference Techniques #Statistical Methods and Inference #Statistical Methods and Bayesian Inference
- AutoML Two-Sample Test
2022/06/17 by Jonas M. Kübler, Kübler, Jonas M., Vincent Stimper +7 · 4 citations
Computer Science · #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- A Witness Two-Sample Test
2021/02/10 by Kübler, Jonas M., Jitkrittum, Wittawat, Schölkopf, Bernhard +1 · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models
2023/05/24 by Siu Lun Chau, Chau, Siu Lun, Krikamol Muandet +3 · 5 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Gaussian Processes and Bayesian Inference #Bayesian Modeling and Causal Inference
- Kernel Mean Shrinkage Estimators
2014/05/21 by Krikamol Muandet, Muandet, Krikamol, Bharath K. Sriperumbudur +7 · 2 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Statistical Methods and Inference #Gaussian Processes and Bayesian Inference
- Minimax Estimation of Kernel Mean Embeddings
2016/02/13 by Ilya Tolstikhin, Tolstikhin, Ilya, Bharath K. Sriperumbudur +3 · 2 citations
Mathematics · #Statistical Methods and Inference #Statistical Methods and Bayesian Inference #Statistical Distribution Estimation and Applications
- Learning from Distributions via Support Measure Machines
2012/02/29 by Krikamol Muandet, Kenji Fukumizu, Muandet, Krikamol +5 · 2 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)
- Design and Analysis of the NIPS 2016 Review Process
2017/08/31 by Shah, Nihar B., Tabibian, Behzad, Muandet, Krikamol +2 · 2 citations
#Digital Libraries (cs.DL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Social and Information Networks (cs.SI)
- Privacy-Preserving Causal Inference via Inverse Probability Weighting
2019/05/29 by Si Kai Lee, Luigi Gresele, Lee, Si Kai +5 · 2 citations
Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
- Learning Kernel Tests Without Data Splitting
2020/06/03 by Jonas M. Kübler, Wittawat Jitkrittum, Kübler, Jonas M. +5 · 2 citations
Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Statistical Methods and Inference
- A Measure-Theoretic Axiomatisation of Causality
2023/05/19 by Junhyung Park, Park, Junhyung, Simon Buchholz +5 · 3 citations
Arts and Humanities · Computer Science · Physics and Astronomy · #Philosophy and History of Science #Computability, Logic, AI Algorithms #Statistical Mechanics and Entropy
- Instrumental Variable Regression via Kernel Maximum Moment Loss
2020/10/15 by Zhang, Rui, Imaizumi, Masaaki, Schölkopf, Bernhard +1 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Credal Two-Sample Tests of Epistemic Uncertainty
2024/10/16 by Siu Lun Chau, Antonin Schrab, Chau, Siu Lun +8 · 2 voices · 3 citations
Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Advanced Causal Inference Techniques #Adversarial Robustness in Machine Learning
- Kernel Conditional Density Operators
2019/05/27 by Schuster, Ingmar, Mollenhauer, Mattes, Klus, Stefan +1 · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Towards a Learning Theory of Cause-Effect Inference
2015/02/09 by David López-Paz, Lopez-Paz, David, Krikamol Muandet +5 · 2 citations
Computer Science · #Bayesian Modeling and Causal Inference #Machine Learning and Algorithms #Blind Source Separation Techniques
- Regularised Least-Squares Regression with Infinite-Dimensional Output Space
2020/10/21 by Park, Junhyunng, Muandet, Krikamol · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- On the Relationship Between Explanation and Prediction: A Causal View
2022/12/13 by Karimi, Amir-Hossein, Muandet, Krikamol, Kornblith, Simon +2 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
- Causal Strategic Learning with Competitive Selection
2023/08/30 by Vo, Kiet Q. H., Aadil, Muneeb, Chau, Siu Lun +1 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences
- Robust Feature Inference: A Test-time Defense Strategy using Spectral Projections
2023/07/21 by Singh, Anurag, Sabanayagam, Mahalakshmi, Muandet, Krikamol +1 · 1 citation
#Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Integral Imprecise Probability Metrics
2025/05/22 by Siu Lun Chau, Michele Caprio, Chau, Siu Lun +3 · 4 citations
Computer Science · #Bayesian Modeling and Causal Inference
- (Im)possibility of Collective Intelligence
2022/06/05 by Krikamol Muandet, Muandet, Krikamol · 1 citation
Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Economics and business #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Theoretical Economics (econ.TH)
- Exact Shapley Attributions in Quadratic-time for FANOVA Gaussian Processes
2025/08/20 by Mohammadi, Majid, Muandet, Krikamol, Tiddi, Ilaria +2 · 3 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)