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- Machine Learning CS 5751 Home Page
- Gaussian processes
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- Gaussian processes for uncertainty quantification
- Introduction to Uncertainty Quantification and Gaussian Processes
- Doron Zeilberger Website About Math
- Bagged Posterior for Robust Inference
- François Fleuret's homepage at the Idiap Research Institute.
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- Comparing Probabilities 2 UAI 2017
- Comparing Probabilities 1 UAI 2017
- The goodness of Fit for Latent Variable Models ICML 2019 Workshop
- GANs with Integrable Probability Metric
- Kernel Test for Goodness of Fit
- Interpretable Two Sample Test
- Two Sample Test NeurIPS 2019
- Measures on Probability Distributions NeurIPS 2019
- Kernel Statistical Test for Independence
- Covariate Shift NIPS Transfer Learning 2009
- Energy Based Models Stanford cs236
- Probabilistic Circuits Stanford 2019
- Graduate Summer School: Intelligent Extraction of Information from Graphs and High Dimensional Data (Schedule) - IPAM
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- MLPR class notes - Machine Learning and Pattern Recognition
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- Introduction to Gaussian Processes
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- An introductory-level textbook in statistics covering descriptive and inferential statistics. Each chapter has links to related texts, instructional demos, and free statistical analysis programs. Author is David M. Lane, Rice University departments of statistics, psychology, and management.
- Optimisation Fall 2019 Iowa State
- 6.253 Convex Analysis and Optimization, Complete Lecture Notes
- Mathematical methods for economic theory: 3.4 Quasiconcavity and quasiconvexity
- Machine Learning Blog Summaries
- Stanford University CS236: Deep Generative Models
- Robust Classification NeurIPS Website
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- Probabilistic Graphical Models, Fall 2007
- Bayesian Deep Learning Workshop | NIPS 2016
публикации (спрятать)2111
- IEEE Transactions on Knowledge and Data Engineering, 28 (12): 3395-3408 (December 2016)
- (2018)
- (2000)
- (2018)cite arxiv:1804.11271Comment: This work substantially extends the work of Matthews et al. (2018) published at the International Conference on Learning Representations (ICLR) 2018.
- (2018)cite arxiv:1810.05148Comment: Published as a conference paper at ICLR 2019.
- (2018)cite arxiv:1803.03635Comment: ICLR camera ready.
- (2019)cite arxiv:1902.06977.
- (2017)cite arxiv:1704.04289Comment: 35 pages, published version (JMLR 2017).
- (2017)cite arxiv:1712.09913Comment: NIPS 2018 (extended version, 10.5 pages), code is available at https://github.com/tomgoldstein/loss-landscape.
- (2016)
