New episode is out, my dear Bayesians! All about #CausalInference, #Experimentation at scale, and #GaussianProcesses -- definitely a fun one!
New Episode Alert!
🎙️ Scaling #BayesianCausalInference with Thomas Pinder, Netflix & creator of GPJax
Essential listening for anyone working at the frontier of Bayes, Experimentation & Causal Inference 📈
🔗 learnbayesstats.com/episode/154-...
#Bayesian #JAX #MachineLearning #CausalInference #GPJax
🎙️ Scaling #BayesianCausalInference with Thomas Pinder, Netflix & creator of GPJax
Essential listening for anyone working at the frontier of Bayes, Experimentation & Causal Inference 📈
🔗 learnbayesstats.com/episode/154-...
#Bayesian #JAX #MachineLearning #CausalInference #GPJax
Bayesian Causal Inference at Scale
Thomas Pinder discusses Bayesian causal inference and Gaussian processes. Explore synthetic control and diff-in-diff for industry
learnbayesstats.com
March 25, 2026 at 2:46 PM
New episode is out, my dear Bayesians! All about #CausalInference, #Experimentation at scale, and #GaussianProcesses -- definitely a fun one!
💻 GitHub: github.com/geometric-ke...
📄 JMLR Paper: www.jmlr.org/papers/v26/2...
#MachineLearning #GeometricDeepLearning #GaussianProcesses #Kernels #Graphs #Manifolds #JMLR #OpenSource
📄 JMLR Paper: www.jmlr.org/papers/v26/2...
#MachineLearning #GeometricDeepLearning #GaussianProcesses #Kernels #Graphs #Manifolds #JMLR #OpenSource
March 12, 2026 at 4:06 PM
Our @pydata.bsky.social tutorial with @fonnesbeck.bsky.social on Mastering #GaussianProcesses with @pymc-devs.bsky.social is now online 🥳
If you missed it live, come check it out!
Enjoy & PyMCheers 🖖
Video: www.youtube.com/watch?v=u6I5...
GitHub repo: github.com/AlexAndorra/...
If you missed it live, come check it out!
Enjoy & PyMCheers 🖖
Video: www.youtube.com/watch?v=u6I5...
GitHub repo: github.com/AlexAndorra/...
Alexandre Andorra & Christopher Fonnesbeck- Mastering Gaussian Processes with PyMC | PyData NYC 2024
YouTube video by PyData
www.youtube.com
December 2, 2024 at 4:04 PM
Our @pydata.bsky.social tutorial with @fonnesbeck.bsky.social on Mastering #GaussianProcesses with @pymc-devs.bsky.social is now online 🥳
If you missed it live, come check it out!
Enjoy & PyMCheers 🖖
Video: www.youtube.com/watch?v=u6I5...
GitHub repo: github.com/AlexAndorra/...
If you missed it live, come check it out!
Enjoy & PyMCheers 🖖
Video: www.youtube.com/watch?v=u6I5...
GitHub repo: github.com/AlexAndorra/...
𝗪𝗵𝗮𝘁 𝗶𝘀 𝗚𝗮𝘂𝘀𝘀𝗶𝗮𝗻 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗥𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻?
Gaussian Processes Regression (GPR) is a powerful machine learning technique used for predicting continuous values, especially when data is limited
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #AI #GaussianProcesses #DataScience
Gaussian Processes Regression (GPR) is a powerful machine learning technique used for predicting continuous values, especially when data is limited
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #AI #GaussianProcesses #DataScience
July 31, 2024 at 5:08 AM
𝗪𝗵𝗮𝘁 𝗶𝘀 𝗚𝗮𝘂𝘀𝘀𝗶𝗮𝗻 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗥𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻?
Gaussian Processes Regression (GPR) is a powerful machine learning technique used for predicting continuous values, especially when data is limited
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #AI #GaussianProcesses #DataScience
Gaussian Processes Regression (GPR) is a powerful machine learning technique used for predicting continuous values, especially when data is limited
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #AI #GaussianProcesses #DataScience
Lightweight & interpretable. No neural components. Effective under sparse sampling.
📄 arXiv: arxiv.org/abs/2604.00862
💻 Code: github.com/POSE-Lab/GP-...
🏛️ ISPRS 2026: isprs2026toronto.com
#3DVision #GaussianProcesses #ShapeRepresentation
📄 arXiv: arxiv.org/abs/2604.00862
💻 Code: github.com/POSE-Lab/GP-...
🏛️ ISPRS 2026: isprs2026toronto.com
#3DVision #GaussianProcesses #ShapeRepresentation
Shape Representation using Gaussian Process mixture models
Traditional explicit 3D representations, such as point clouds and meshes, demand significant storage to capture fine geometric details and require complex indexing systems for surface lookups, making ...
arxiv.org
April 2, 2026 at 7:57 PM
Lightweight & interpretable. No neural components. Effective under sparse sampling.
📄 arXiv: arxiv.org/abs/2604.00862
💻 Code: github.com/POSE-Lab/GP-...
🏛️ ISPRS 2026: isprs2026toronto.com
#3DVision #GaussianProcesses #ShapeRepresentation
📄 arXiv: arxiv.org/abs/2604.00862
💻 Code: github.com/POSE-Lab/GP-...
🏛️ ISPRS 2026: isprs2026toronto.com
#3DVision #GaussianProcesses #ShapeRepresentation
This one is a very practical one, with the great Maurizio Filippone -- all about the intersection of #DeepLearning , #GaussianProcesses and why combining them is so powerful. Enjoy!
Bayesian deep learning helps ML models understand their uncertainty
In this episode @alex-andorra.bsky.social talks with Maurizio Filippone about Gaussian Processes, scalable inference, MCMC, and Bayesian deep learning at scale
🎧 learnbayesstats.com/episode/144-...
#BayesianStats #AI #ML #Bayes
In this episode @alex-andorra.bsky.social talks with Maurizio Filippone about Gaussian Processes, scalable inference, MCMC, and Bayesian deep learning at scale
🎧 learnbayesstats.com/episode/144-...
#BayesianStats #AI #ML #Bayes
November 3, 2025 at 4:14 PM
This one is a very practical one, with the great Maurizio Filippone -- all about the intersection of #DeepLearning , #GaussianProcesses and why combining them is so powerful. Enjoy!
What are Gaussian Processes?
Gaussian Processes (GP) are powerful statistical models used in machine learning to predict and analyze complex data.
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #GaussianProcesses #DataScience #AI #Regression #Classification
Gaussian Processes (GP) are powerful statistical models used in machine learning to predict and analyze complex data.
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #GaussianProcesses #DataScience #AI #Regression #Classification
July 30, 2024 at 5:32 AM
What are Gaussian Processes?
Gaussian Processes (GP) are powerful statistical models used in machine learning to predict and analyze complex data.
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #GaussianProcesses #DataScience #AI #Regression #Classification
Gaussian Processes (GP) are powerful statistical models used in machine learning to predict and analyze complex data.
Learn more : www.aionlinecourse.com/ai-basics/ga...
#MachineLearning #GaussianProcesses #DataScience #AI #Regression #Classification
Awesome work! Just came across @motonobu-kanagawa & colleagues‘ monograph on #GaussianProcesses and reproducing kernel #HilbertSpace methods. Discusses the deep mathematical equivalence between GP inference and kernel-based #regularization in #RKHSs. Definitely one for the reading list!
We've written a monograph on Gaussian processes and reproducing kernel methods (with @philipphennig.bsky.social, @sejdino.bsky.social and Bharath Sriperumbudur).
arxiv.org/abs/2506.17366
arxiv.org/abs/2506.17366
Gaussian Processes and Reproducing Kernels: Connections and Equivalences
This monograph studies the relations between two approaches using positive definite kernels: probabilistic methods using Gaussian processes, and non-probabilistic methods using reproducing kernel Hilb...
arxiv.org
July 29, 2026 at 6:10 PM
Awesome work! Just came across @motonobu-kanagawa & colleagues‘ monograph on #GaussianProcesses and reproducing kernel #HilbertSpace methods. Discusses the deep mathematical equivalence between GP inference and kernel-based #regularization in #RKHSs. Definitely one for the reading list!
A compact nonstationary kernel lets exact Gaussian processes handle over 1 million data points, improving climate temperature forecasts versus scalable approximations. Read more: https://getnews.me/exact-gaussian-processes-with-compact-nonstationary-kernels/ #gaussianprocesses #nonstationary
September 20, 2025 at 3:35 PM
A compact nonstationary kernel lets exact Gaussian processes handle over 1 million data points, improving climate temperature forecasts versus scalable approximations. Read more: https://getnews.me/exact-gaussian-processes-with-compact-nonstationary-kernels/ #gaussianprocesses #nonstationary
A side from these projects, I collaborate on a number of projects involving tracking, sensor and data fusion in a variety of domains.
I am interested in #machinelearning #ML, #gaussianprocesses and #bayesianoptimisation (some papers might come around in the new year).
I am interested in #machinelearning #ML, #gaussianprocesses and #bayesianoptimisation (some papers might come around in the new year).
November 18, 2024 at 3:18 PM
A side from these projects, I collaborate on a number of projects involving tracking, sensor and data fusion in a variety of domains.
I am interested in #machinelearning #ML, #gaussianprocesses and #bayesianoptimisation (some papers might come around in the new year).
I am interested in #machinelearning #ML, #gaussianprocesses and #bayesianoptimisation (some papers might come around in the new year).
It was great having @carlhenrikek here in Genova! #gaussianprocesses #MachineLearning @malga_center #malgaseminars #thankful
January 21, 2025 at 2:59 PM
It was great having @carlhenrikek here in Genova! #gaussianprocesses #MachineLearning @malga_center #malgaseminars #thankful
EzTaoX: Unlock the secrets of supermassive black holes with scalable Gaussian Process modeling for AGN light curves across multiple wavelengths and surveys
🔗 https://github.com/LSST-AGN-Variability/EzTaoX
#ActiveGalacticNuclei #GaussianProcesses #TimeSeries
🔗 https://github.com/LSST-AGN-Variability/EzTaoX
#ActiveGalacticNuclei #GaussianProcesses #TimeSeries
February 4, 2026 at 9:01 AM
EzTaoX: Unlock the secrets of supermassive black holes with scalable Gaussian Process modeling for AGN light curves across multiple wavelengths and surveys
🔗 https://github.com/LSST-AGN-Variability/EzTaoX
#ActiveGalacticNuclei #GaussianProcesses #TimeSeries
🔗 https://github.com/LSST-AGN-Variability/EzTaoX
#ActiveGalacticNuclei #GaussianProcesses #TimeSeries
Reviews GP scaling methods: low-rank, tapering, divide-conquer, Vecchia. All reduce cubic to linear cost, but MCMC still needs thousands of iterations. #gaussianprocesses
How Spatial Scientists Are Solving the Gaussian Process Scaling Challenge
hackernoon.com
May 31, 2025 at 9:52 AM
Reviews GP scaling methods: low-rank, tapering, divide-conquer, Vecchia. All reduce cubic to linear cost, but MCMC still needs thousands of iterations. #gaussianprocesses
SGMCMC + Vecchia approximation enables scalable Bayesian GP inference for large spatial datasets, achieving linear time complexity and competitive performance. #gaussianprocesses
Stochastic Gradient MCMC for Large-Scale Gaussian Process Spatial Modeling
hackernoon.com
May 31, 2025 at 9:38 AM
SGMCMC + Vecchia approximation enables scalable Bayesian GP inference for large spatial datasets, achieving linear time complexity and competitive performance. #gaussianprocesses
At a workshop at Albert Einstein Institute and finally finished giving my tutorial and talk on #GaussianProcesses and using them for modeling #gravitationalwaves. I had to then treat myself to a local German beer 😍
November 19, 2024 at 2:35 PM
At a workshop at Albert Einstein Institute and finally finished giving my tutorial and talk on #GaussianProcesses and using them for modeling #gravitationalwaves. I had to then treat myself to a local German beer 😍