Канал: Gaussian Process Summer School

GPSS 2024 Transfer Learning Gaussian Processes for DNA Design

GPSS 2024 Transfer Learning Gaussian Processes for DNA Design

GPSS2024 Using GP emulation in cardiovascular modelling

GPSS2024 Using GP emulation in cardiovascular modelling

GPSS2024 Emulating cohorts of cardiac digital twins using Gaussian Processes

GPSS2024 Emulating cohorts of cardiac digital twins using Gaussian Processes

GPSS2024 Multi-task Gaussian processes

GPSS2024 Multi-task Gaussian processes

GPSS2024 Bayesian Optimization and Beyond

GPSS2024 Bayesian Optimization and Beyond

GPSS2024 Biological applications of Gaussian process modelling

GPSS2024 Biological applications of Gaussian process modelling

GPSS2024 From geostatistics to graphs: Gaussian processes in practice

GPSS2024 From geostatistics to graphs: Gaussian processes in practice

GPSS2024 Gaussian processes and non-Gaussian likelihoods

GPSS2024 Gaussian processes and non-Gaussian likelihoods

GPSS2024: A first introduction to Gaussian processes

GPSS2024: A first introduction to Gaussian processes

GPSS2024: Adjoint aided inference of Gaussian process driven differential equations

GPSS2024: Adjoint aided inference of Gaussian process driven differential equations

GPSS2024: A second introduction to Gaussian processes

GPSS2024: A second introduction to Gaussian processes

Robust Empirical Bayes for Gaussian Processes

Robust Empirical Bayes for Gaussian Processes

Bayesian Optimization and Beyond

Bayesian Optimization and Beyond

A conversation with Neil Lawrence

A conversation with Neil Lawrence

Computationally efficient GPs

Computationally efficient GPs

Latent space geometry

Latent space geometry

Deep generative modelling aiding GPs and spatial statistics

Deep generative modelling aiding GPs and spatial statistics

Gaussian Process Emulators for Cardiac Digital Twins: Enabling Scalable Patient-Specific Modeling

Gaussian Process Emulators for Cardiac Digital Twins: Enabling Scalable Patient-Specific Modeling

Modelling London’s Air Quality Using Spatio-Temporal Gaussian Processes

Modelling London’s Air Quality Using Spatio-Temporal Gaussian Processes

Identifying Dynamic Systems for Digital Twins of Engineering Assets

Identifying Dynamic Systems for Digital Twins of Engineering Assets

Bayesian Surrogate Modelling of Computer Experiments using Gaussian Processes

Bayesian Surrogate Modelling of Computer Experiments using Gaussian Processes

Multi-task Gaussian processes

Multi-task Gaussian processes

Introduction to Gaussian Processes

Introduction to Gaussian Processes

A second introduction to Gaussian Processes

A second introduction to Gaussian Processes

Bayesian Optimization: From Research to Production with BoTorch & Ax

Bayesian Optimization: From Research to Production with BoTorch & Ax

Reliable Deep Learning with Edward2 & Uncertainty Baselines

Reliable Deep Learning with Edward2 & Uncertainty Baselines

Opensource tools at Secondmind

Opensource tools at Secondmind

Challenges in building widely applicable GP software

Challenges in building widely applicable GP software

Overview of GPy

Overview of GPy

GPSS 2021: Emulation

GPSS 2021: Emulation

GPSS 2021: Intro to Bayes Opt

GPSS 2021: Intro to Bayes Opt

GPSS 2021: Unsupervised and composite GPs

GPSS 2021: Unsupervised and composite GPs

GPSS 2021: Multioutput GPs

GPSS 2021: Multioutput GPs

GPSS 2021: GPs for non-Gaussian likelihoods

GPSS 2021: GPs for non-Gaussian likelihoods

GPSS 2021: Scalability of GPs

GPSS 2021: Scalability of GPs

GPSS 2021: Spectral kernels

GPSS 2021: Spectral kernels

GPSS 2021: Kernel design

GPSS 2021: Kernel design

GPSS 2021: Introduction to GPs

GPSS 2021: Introduction to GPs

Causal decision-making meets Gaussian Processes

Causal decision-making meets Gaussian Processes

A class of algorithms for general instrumental variable models

A class of algorithms for general instrumental variable models

Non-statistical notions of independence in causal discovery

Non-statistical notions of independence in causal discovery

Causal discovery: methodology, evaluation and application

Causal discovery: methodology, evaluation and application

Causal Inference: An Overview and the Role of Probabilistic Modelling

Causal Inference: An Overview and the Role of Probabilistic Modelling

Bayesian Neural Networks from a Gaussian Process Perspective

Bayesian Neural Networks from a Gaussian Process Perspective

Introduction to Bayesian Optimisation

Introduction to Bayesian Optimisation

Deep Gaussian processes

Deep Gaussian processes

Multi-task Gaussian process modelling for point process data

Multi-task Gaussian process modelling for point process data

Unsupervised learning and composite GPs

Unsupervised learning and composite GPs

Scalable Gaussian processes

Scalable Gaussian processes

Representation Learning with Gaussian Processes

Representation Learning with Gaussian Processes

Kernel design

Kernel design

Introduction to Gaussian processes

Introduction to Gaussian processes

Gaussian Process Summer School Live Stream

Gaussian Process Summer School Live Stream

GPSS2019 - Invariances in Gaussian processes and how to learn them

GPSS2019 - Invariances in Gaussian processes and how to learn them

GPSS2019 - Active Multi-Information Source Bayesian Quadrature

GPSS2019 - Active Multi-Information Source Bayesian Quadrature

GPSS2019 - Constraining Gaussian Processes by Variational Fourier Features

GPSS2019 - Constraining Gaussian Processes by Variational Fourier Features

GPSS2019 - State Space Methods for temporal GPs

GPSS2019 - State Space Methods for temporal GPs

GPSS2019 - Introduction to Bayesian Optimisation

GPSS2019 - Introduction to Bayesian Optimisation

GPSS2019 - Unsupervised learning and Deep GPs

GPSS2019 - Unsupervised learning and Deep GPs

GPSS2019 - Bayesian Neural Networks: a function space view tour

GPSS2019 - Bayesian Neural Networks: a function space view tour

GPSS2019 - Introduction to Deep GPs

GPSS2019 - Introduction to Deep GPs

GPSS2019 - Gaussian Processes and Non-Gaussian Likelihoods

GPSS2019 - Gaussian Processes and Non-Gaussian Likelihoods

GPSS2019 - Computationally efficient GPs

GPSS2019 - Computationally efficient GPs

GPSS2019 - Kernel Design

GPSS2019 - Kernel Design

GPSS2019 - Introduction to Gaussian Processes

GPSS2019 - Introduction to Gaussian Processes