Sejdinovic, Dino
- Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
2018/07/06 by Kanagawa, Motonobu, Hennig, Philipp, Sejdinovic, Dino +1 · 21 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Fast Two-Sample Testing with Analytic Representations of Probability\n Measures
2015/06/15 by Kacper Chwialkowski, Chwialkowski, Kacper, Aaditya Ramdas +5 · 10 citations
Computer Science · Decision Sciences · Mathematics · #62G10 #Advanced Bandit Algorithms Research #Algorithms and Data Compression #FOS: Computer and information sciences #G.3 #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Methods and Inference
- RKHS-SHAP: Shapley Values for Kernel Methods
2021/10/18 by Chau, Siu Lun, Hu, Robert, Gonzalez, Javier +1 · 10 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Survival Regression with Proper Scoring Rules and Monotonic Neural Networks
2021/03/26 by David Rindt, Robert Hu, Rindt, David +5 · 6 citations
Mathematics · #Statistical Methods and Inference #Statistical Methods and Bayesian Inference
- A Wild Bootstrap for Degenerate Kernel Tests
2014/08/23 by Kacper Chwialkowski, Chwialkowski, Kacper, Dino Sejdinović +3 · 4 citations
Computer Science · Economics, Econometrics and Finance · Mathematics · #62G10 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Machine Learning (stat.ML) #Statistical Methods and Inference
- A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods
2023/05/24 by Wild, Veit David, Ghalebikesabi, Sahra, Sejdinovic, Dino +1 · 7 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
- Deconditional Downscaling with Gaussian Processes
2021/05/27 by Siu Lun Chau, Chau, Siu Lun, Shahine Bouabid +3 · 5 citations
Computer Science · Environmental Science · #Atmospheric and Environmental Gas Dynamics #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Remote Sensing in Agriculture
- Bayesian Learning of Kernel Embeddings
2016/03/07 by Seth Flaxman, Flaxman, Seth, Dino Sejdinović +5 · 4 citations
Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Bayesian Methods and Mixture Models #Statistical Methods and Inference
- A Kernel Test for Three-Variable Interactions
2013/06/10 by Sejdinovic, Dino, Gretton, Arthur, Bergsma, Wicher · 2 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
- 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
- Variational Learning on Aggregate Outputs with Gaussian Processes
2018/05/22 by Ho Chung Leon Law, Dino Sejdinović, Law, Ho Chung Leon +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)
- Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features
2017/11/15 by Jean-François Ton, Seth Flaxman, Ton, Jean-Francois +5 · 2 citations
Computer Science · Engineering · Environmental Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Remote Sensing in Agriculture #Remote-Sensing Image Classification
- Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning
2022/05/12 by Wild, Veit D., Hu, Robert, Sejdinovic, Dino · 3 citations
#Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
- Probabilistic Integration: A Role in Statistical Computation?
2015/12/03 by Briol, François-Xavier, Oates, Chris. J., Girolami, Mark +2 · 2 citations
#Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Statistics Theory (math.ST)
- Hyperparameter Learning via Distributional Transfer
2018/10/15 by Law, Ho Chung Leon, Zhao, Peilin, Chan, Lucian +2 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- BayesIMP: Uncertainty Quantification for Causal Data Fusion
2021/06/07 by Siu Lun Chau, Chau, Siu Lun, Jean-François Ton +7 · 3 citations
Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Learning Inconsistent Preferences with Gaussian Processes
2020/06/06 by Siu Lun Chau, Chau, Siu Lun, Javier González +3 · 2 citations
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Spectral Ranking with Covariates
2020/05/08 by Chau, Siu Lun, Cucuringu, Mihai, Sejdinovic, Dino · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes
2021/06/02 by Wild, Veit, Kanagawa, Motonobu, Sejdinovic, Dino · 2 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
- Credal Two-Sample Tests of Epistemic Uncertainty
2024/10/16 by Siu Lun Chau, Chau, Siu Lun, Antonin Schrab +8 · 2 voices · 3 citations
Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Advanced Causal Inference Techniques #Adversarial Robustness in Machine Learning
- FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation
2023/07/14 by Shahine Bouabid, Dino Sejdinović, Bouabid, Shahine +3 · 3 citations
Computer Science · Decision Sciences · #Applications (stat.AP) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Neural Networks and Applications #Simulation Techniques and Applications
- 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)
- A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment
2021/11/25 by Hu, Robert, Sejdinovic, Dino, Evans, Robin J. · 2 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
- Poisson intensity estimation with reproducing kernels
2016/10/27 by Flaxman, Seth, Teh, Yee Whye, Sejdinovic, Dino · 1 citation
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Causal Inference via Kernel Deviance Measures
2018/04/12 by Mitrovic, Jovana, Sejdinovic, Dino, Teh, Yee Whye · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
- Gaussian Processes and Reproducing Kernels: Connections and Equivalences
2025/06/20 by Motonobu Kanagawa, Kanagawa, Motonobu, Philipp Hennig +5 · 3 voices · 4 citations
#stat.ML #cs.LG #math.NA #math.PR #math.ST
- Squared Neural Families: A New Class of Tractable Density Models
2023/05/22 by Tsuchida, Russell, Ong, Cheng Soon, Sejdinovic, Dino · 2 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- 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)
- Giga-scale Kernel Matrix Vector Multiplication on GPU
2022/02/02 by Hu, Robert, Chau, Siu Lun, Sejdinovic, Dino +1 · 1 citation
#Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Mathematical Software (cs.MS) #Numerical Analysis (math.NA)
- Kernel Biclustering algorithm in Hilbert Spaces
2022/08/07 by Marcos Matabuena, J. C Vidal, Matabuena, Marcos +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Gene expression and cancer classification #Machine Learning (stat.ML) #Metabolomics and Mass Spectrometry Studies #Methodology (stat.ME) #Statistical Methods and Inference #Statistics Theory (math.ST)
- Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families
2024/02/14 by Russell Tsuchida, Tsuchida, Russell, Cheng Soon Ong +3 · 1 citation
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- Hamiltonian Variational Auto-Encoder
2018/05/29 by Anthony L. Caterini, Caterini, Anthony L., Arnaud Doucet +3 · 1 citation
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis
- Squared families: Searching beyond regular probability models
2025/03/27 by Tsuchida, Russell, Liu, Jiawei, Ong, Cheng Soon +1 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)