Publication

This page contains a list of my publications in a chronological order. If you have questions regarding any of these publications, please do not hesitate to contact me directly.

My bibliographic information are also available on Google Scholar, DBLP, and Semantic Scholar.

2023

• Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes
  Junhyung Park - Krikamol Muandet
  Algorithmic Learning Theory (ALT 2023)
• Gated Domain Units for Multi-source Domain Generalization
  Simon Föll - Alina Dubatovka - Eugen Ernst - Martin Maritsch - Patrik Okanovic - Gudrun Thäter - Joachim Buhmann - Felix Wortmann - Krikamol Muandet
  Preprint
• Impossibility of Collective Intelligence
  Krikamol Muandet
  Preprint
• Learning Counterfactually Invariant Predictors
  Francesco Quinzan - Cecilia Casolo - Krikamol Muandet - Yucen Luo - Niki Kilbertus
  Preprint
• On the Relationship Between Explanation and Prediction: A Causal View
  Amir-Hossein Karimi - Krikamol Muandet - Simon Kornblith - Bernhard Schölkopf - Been Kim
  Preprint
• Instrumental Variable Regression via Kernel Maximum Moment Loss
  Rui Zhang - Masaaki Imaizumi - Bernhard Schölkopf - Krikamol Muandet
  Journal of Causal Inference (JCI)

2022

• A Witness Two-Sample Test
  Jonas Kübler - Wittawat Jitkrittum - Bernhard Schölkopf - Krikamol Muandet
  International Conference on Artificial Intelligence and Statistics (AISTATS 2022)
• Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions
  Heiner Kremer - Jia-Jie Zhu - Krikamol Muandet - Bernhard Schölkopf
  International Conference on Machine Learning (ICML 2022)
• AutoML Two-Sample Test
  Jonas Kübler - Vincent Stimper - Simon Buchholz - Krikamol Muandet - Bernhard Schölkopf
  Neural Information Processing Systems (NeurIPS 2022)

2021

• An Optimal Witness Function for Two-Sample Testing
  Jonas Kübler - Wittawat Jitkrittum - Bernhard Schölkopf - Krikamol Muandet
  Preprint
• Maximum Moment Restriction for Instrumental Variable Regression
  Rui Zhang - Masaaki Imaizumi - Bernhard Schölkopf - Krikamol Muandet
  Preprint
• Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
  Junhyung Park - Uri Shalit - Bernhard Schölkopf - Krikamol Muandet
  International Conference on Machine Learning (ICML 2021)
• Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
  Afsaneh Mastouri - Yuchen Zhu - Limor Gultchin - Anna Korba - Ricardo Silva - Matt Kusner - Arthur Gretton - Krikamol Muandet
  International Conference on Machine Learning (ICML 2021)
• Counterfactual Mean Embeddings
  Krikamol Muandet - Motonobu Kanagawa - Sorawit Saengkyongam - Sanparith Marukatat
  Journal of Machine Learning Research (JMLR)

2020

• Grasping Field: Learning Implicit Representations for Human Grasps
  Korrawe Karunratanakul - Jinlong Yang - Yan Zhang - Michael Black - Krikamol Muandet - Siyu Tang
  International Conference on 3D Vision (3DV 2020)
  * Best Paper Award
• Fair Decisions Despite Imperfect Predictions
  Niki Kilbertus - Manuel Gomez Rodriguez - Bernhard Schölkopf - Krikamol Muandet - Isabel Valera
  International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
• Kernel Conditional Density Operators
  Ingmar Schuster - Mattes Mollenhauer - Stefan Klus - Krikamol Muandet
  International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
• A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming
  Jia-Jie Zhu - Krikamol Muandet - Moritz Diehl - Bernhard Schölkopf
  World Congress of the International Federation of Automatic Control (IFAC 2020)
• MATE: Plugging in Model Awareness to Task Embedding for Meta Learning
  Xiaohan Chen - Zhangyang Wang - Siyu Tang - Krikamol Muandet
  Neural Information Processing Systems (NeurIPS 2020)
• Dual Instrumental Variable Regression
  Krikamol Muandet - Arash Mehrjou - Si Kai Lee - Anant Raj
  Neural Information Processing Systems (NeurIPS 2020)
• Learning Kernel Tests Without Data Splitting
  Jonas Kübler - Wittawat Jitkrittum - Bernhard Schölkopf - Krikamol Muandet
  Neural Information Processing Systems (NeurIPS 2020)
• A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
  Junhyung Park - Krikamol Muandet
  Neural Information Processing Systems (NeurIPS 2020)
• Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
  Stefan Klus - Ingmar Schuster - Krikamol Muandet
  Journal of Nonlinear Science
• Kernel Conditional Moment Test via Maximum Moment Restriction
  Krikamol Muandet - Wittawat Jitkrittum - Jonas Kübler
  The Conference on Uncertainty in Artificial Intelligence (UAI 2020)

2019

• Kernel-Guided Training of Implicit Generative Models with Stability Guarantees
  Arash Mehrjou - Wittawat Jitkrittum - Krikamol Muandet - Bernhard Schölkopf
  Preprint
• Low-rank Random Tensor for Bilinear Pooling
  Yan Zhang - Krikamol Muandet - Qianli Ma - Heiko Neumann - Siyu Tang
  Preprint
• Private Causal Inference using Propensity Scores
  Si Kai Lee - Luigi Gresele - Mijung Park - Krikamol Muandet
  Preprint
• Local Temporal Bilinear Pooling for Fine-grained Action Parsing
  Yan Zhang - Siyu Tang - Krikamol Muandet - Christian Jarvers - Heiko Neumann
  IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2019)
• Quantum Mean Embedding of Probability Distributions
  Jonas Kübler - Krikamol Muandet - Bernhard Schölkopf
  Physical Review Research (PRR)

2018

• Counterfactual Mean Embeddings
  Krikamol Muandet - Motonobu Kanagawa - Sorawit Saengkyongam - Sanparith Marukatat
  Preprint
• Design and Analysis of the NIPS 2016 Review Process
  Nihar Shah - Behzad Tabibian - Krikamol Muandet - Isabelle Guyon - Ulrike von Luxburg
  Journal of Machine Learning Research (JMLR)

2017

• Dagstuhl Seminar: New Directions for Learning with Kernels and Gaussian Processes
  Arthur Gretton - Philipp Hennig - Carl Rasmussen - Bernhard Schölkopf
  Report of Dagstuhl Seminar 16481 (contributed talk on kernel mean shrinkage estimators)
• Kernel Mean Embedding of Distributions: A Review and Beyond
  Krikamol Muandet - Kenji Fukumizu - Bharath Sriperumbudur - Bernhard Schölkopf
  Foundations and Trends® in Machine Learning (FnT ML)
• Minimax Estimation of Kernel Mean Embeddings
  Ilya Tolstikhin - Bharath Sriperumbudur - Krikamol Muandet
  Journal of Machine Learning Research (JMLR)

2016

• TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification
  Rohit Babber - Krikamol Muandet - Bernhard Schölkopf
  SIAM International Conference on Data Mining (SDM 2016)

2015

• Towards a Learning Theory of Cause-Effect Inference
  David Lopez-Paz - Krikamol Muandet - Bernhard Schölkopf - Ilya Tolstikhin
  International Conference on Machine Learning (ICML 2015)
• Kernel Mean Shrinkage Estimators
  Krikamol Muandet - Bharath Sriperumbudur - Kenji Fukumizu - Arthur Gretton - Bernhard Schölkopf
  Journal of Machine Learning Research (JMLR)
• Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations
  Bernhard Schölkopf - Krikamol Muandet - Kenji Fukumizu - Jonas Peters
  Statistics and Computing (STAT COMPUT)
• From Points to Probability Measures: Statistical Learning on Distributions with Kernel Mean Embedding
  Krikamol Muandet
  Ph.D. Thesis. Department of Computer Science, University of Tübingen

2014

• Kernel Mean Estimation and Stein Effect
  Krikamol Muandet - Kenji Fukumizu - Bharath Sriperumbudur - Arthur Gretton - Bernhard Schölkopf
  International Conference on Machine Learning (ICML 2014)
• The Randomized Causation Coefficient
  David Lopez-Paz - Krikamol Muandet - Benjamin Recht
  Journal of Machine Learning Research (JMLR)
• Kernel Mean Estimation via Spectral Filtering
  Krikamol Muandet - Bharath Sriperumbudur - Bernhard Schölkopf
  Neural Information Processing Systems (NeurIPS 2014)
• Single-Source Domain Adaptation with Target and Conditional Shift
  Kun Zhang - Bernhard Schölkopf - Krikamol Muandet - Zhikun Wang - Zhi-Hua Zhou - Claudio Persello
  Regularization, Optimization, Kernels, and Support Vector Machines
• A Permutation-based Kernel Conditional Independence Test
  Gary Doran - Krikamol Muandet - Kun Zhang - Bernhard Schölkopf
  The Conference on Uncertainty in Artificial Intelligence (UAI 2014)

2013

• Domain Adaptation under Target and Conditional Shift
  Kun Zhang - Bernhard Schölkopf - Krikamol Muandet - Zhikun Wang
  International Conference on Machine Learning (ICML 2013)
• Domain Generalization via Invariant Feature Representation
  Krikamol Muandet - David Balduzzi - Bernhard Schölkopf
  International Conference on Machine Learning (ICML 2013)
• One-class Support Measure Machines for Group Anomaly Detection
  Krikamol Muandet - Bernhard Schölkopf
  The Conference on Uncertainty in Artificial Intelligence (UAI 2013)

2012

• Learning from Distributions via Support Measure Machines
  Krikamol Muandet - Kenji Fukumizu - Francesco Dinuzzo - Bernhard Schölkopf
  Neural Information Processing Systems (NeurIPS 2012)
  * Spotlight Talk
• Hilbert Space Embedding for Dirichlet Process Mixtures
  Krikamol Muandet
  NeurIPS2012 Workshop on Confluence between Kernel Methods and Graphical Models

2010

• Infinite Independent Subspace Analysis
  Krikamol Muandet - Yee Whye Teh
  M.Sc. Thesis, Department of Computer Science, University College London, 2010.

2009

• Query Selection via Weighted Entropy for Graph-Based Semi-supervised Classification
  Krikamol Muandet - Sanparith Marukatat - Cholwich Nattee
  Asian Conference on Machine Learning (ACML 2009)
• Robust Graph Hyperparameter Learning for Graph Based Semi-supervised Classification
  Krikamol Muandet - Sanparith Marukatat - Cholwich Nattee
  Pacific-Asia Conference on Knowledge Discovery and Data Mining Conference (PAKDD 2009)

2008

• PACS (Picture Archiving Communication System) for Dentistry
  Nakintorn Patanachai - Bunyarit Uyyanonvara - Chanjira Sinthanayothin - Wichit Tharanon - Palakon Sompot - Krikamol Muandet
  International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2008)

2007

• Development of Dental Software: Introducing ADTEC DICOM Viewer
  Nakintorn Patanachai - Bunyarit Uyyanonvara - Chanjira Sinthanayothin - Wichit Tharanon - Palakon Sompot - Krikamol Muandet