the other important aspect is using quasilikelihood/robust standard errors so it doesn't matter if the variance is misspecified, and the log link function is canonical for Poisson GLMs so it'll provide good estimates of the conditional mean
October 24, 2025 at 4:31 AM
the other important aspect is using quasilikelihood/robust standard errors so it doesn't matter if the variance is misspecified, and the log link function is canonical for Poisson GLMs so it'll provide good estimates of the conditional mean
🌾 We had a great time talking about initial data analysis, chi-square goodness of fit and glms with @weihaolipatrick.bsky.social @emitanaka.org 📊🍫👩💻 Thanks for having us @futurecropsau.bsky.social 🙏
October 21, 2025 at 5:03 AM
🌾 We had a great time talking about initial data analysis, chi-square goodness of fit and glms with @weihaolipatrick.bsky.social @emitanaka.org 📊🍫👩💻 Thanks for having us @futurecropsau.bsky.social 🙏
All in all, we believe that GPN-Star offers a scalable & flexible approach for training effective gLMs.
This work was led by my talented students @czye.bsky.social and @gonzalobenegas.bsky.social, with contributions from other lab members, @peterdfields.bsky.social at Jax, & B. Clarke at DKFZ
(n/n)
This work was led by my talented students @czye.bsky.social and @gonzalobenegas.bsky.social, with contributions from other lab members, @peterdfields.bsky.social at Jax, & B. Clarke at DKFZ
(n/n)
September 22, 2025 at 5:29 AM
All in all, we believe that GPN-Star offers a scalable & flexible approach for training effective gLMs.
This work was led by my talented students @czye.bsky.social and @gonzalobenegas.bsky.social, with contributions from other lab members, @peterdfields.bsky.social at Jax, & B. Clarke at DKFZ
(n/n)
This work was led by my talented students @czye.bsky.social and @gonzalobenegas.bsky.social, with contributions from other lab members, @peterdfields.bsky.social at Jax, & B. Clarke at DKFZ
(n/n)
behavior for GLMs. [5/5 of https://arxiv.org/abs/2503.21968v1]
March 31, 2025 at 6:18 AM
behavior for GLMs. [5/5 of https://arxiv.org/abs/2503.21968v1]
Extending the Theta forecasting method to GLMs, GAMs, GLMBOOST and attention: benchmarking on Tourism, M1, M3 and M4 competition data sets (28000 series)
https://thierrymoudiki.github.io/blog/2025/04/14/r/theta-M1-M3-M4
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/04/14/r/theta-M1-M3-M4
#Techtonique #DataScience #Python #rstats #MachineLearning
April 26, 2025 at 7:35 PM
Extending the Theta forecasting method to GLMs, GAMs, GLMBOOST and attention: benchmarking on Tourism, M1, M3 and M4 competition data sets (28000 series)
https://thierrymoudiki.github.io/blog/2025/04/14/r/theta-M1-M3-M4
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/04/14/r/theta-M1-M3-M4
#Techtonique #DataScience #Python #rstats #MachineLearning
Extending the Theta forecasting method to GLMs and attention
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
September 9, 2025 at 9:12 AM
Extending the Theta forecasting method to GLMs and attention
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
Ruijian Han, Lan Luo, Yuanhang Luo, Yuanyuan Lin, Jian Huang
Adaptive debiased SGD in high-dimensional GLMs with streaming data
https://arxiv.org/abs/2405.18284
Adaptive debiased SGD in high-dimensional GLMs with streaming data
https://arxiv.org/abs/2405.18284
June 4, 2024 at 7:01 AM
Ruijian Han, Lan Luo, Yuanhang Luo, Yuanyuan Lin, Jian Huang
Adaptive debiased SGD in high-dimensional GLMs with streaming data
https://arxiv.org/abs/2405.18284
Adaptive debiased SGD in high-dimensional GLMs with streaming data
https://arxiv.org/abs/2405.18284
This whole "challenge yourself" stuff is overrated, I just wanna fit glms and write pdf reports in R for a couple months
November 17, 2023 at 4:41 AM
This whole "challenge yourself" stuff is overrated, I just wanna fit glms and write pdf reports in R for a couple months
alguém vai alí ajustar minhas glms por mim
September 4, 2024 at 4:32 PM
alguém vai alí ajustar minhas glms por mim
Extending the Theta forecasting method to GLMs and attention (in Python and R):
thierrymoudiki.github.io/blog/2025/04...
#rstats #Python
thierrymoudiki.github.io/blog/2025/04...
#rstats #Python
April 8, 2025 at 5:40 PM
Extending the Theta forecasting method to GLMs and attention (in Python and R):
thierrymoudiki.github.io/blog/2025/04...
#rstats #Python
thierrymoudiki.github.io/blog/2025/04...
#rstats #Python
Bo Fu, Dandan Jiang: Unifiedly Efficient Inference on All-Dimensional Targets for Large-Scale GLMs https://arxiv.org/abs/2511.06070 https://arxiv.org/pdf/2511.06070 https://arxiv.org/html/2511.06070
November 11, 2025 at 6:53 AM
Bo Fu, Dandan Jiang: Unifiedly Efficient Inference on All-Dimensional Targets for Large-Scale GLMs https://arxiv.org/abs/2511.06070 https://arxiv.org/pdf/2511.06070 https://arxiv.org/html/2511.06070
GLMs, it upper-bounds the Rademacher complexity by the intrinsic dimensionality of the data manifold. Through extensive experiments on Fundus segmentation and 2D MRI prostate segmentation benchmarks, we show that LangDAug outperforms state-of-the-art [5/6 of https://arxiv.org/abs/2505.19659v1]
May 27, 2025 at 6:35 AM
GLMs, it upper-bounds the Rademacher complexity by the intrinsic dimensionality of the data manifold. Through extensive experiments on Fundus segmentation and 2D MRI prostate segmentation benchmarks, we show that LangDAug outperforms state-of-the-art [5/6 of https://arxiv.org/abs/2505.19659v1]
Two generalized linear methods (GLMs), two fairly exotic machine learning methods (k-nearest neighbors and Gaussian process regression), and two canonical machine learning ensembles (random forests and extra trees). The GLMs are pathetic; all four machine learning methods work reasonably well.
March 12, 2025 at 10:05 PM
Two generalized linear methods (GLMs), two fairly exotic machine learning methods (k-nearest neighbors and Gaussian process regression), and two canonical machine learning ensembles (random forests and extra trees). The GLMs are pathetic; all four machine learning methods work reasonably well.
link 📈🤖
Bayesian inference for generalized linear models via quasi-posteriors () Generalized linear models (GLMs) are routinely used for modeling
relationships between a response variable and a set of covariates. The simple
form of a GLM comes with easy interpretability, but also leads to concern
Bayesian inference for generalized linear models via quasi-posteriors () Generalized linear models (GLMs) are routinely used for modeling
relationships between a response variable and a set of covariates. The simple
form of a GLM comes with easy interpretability, but also leads to concern
January 17, 2025 at 2:08 AM
link 📈🤖
Bayesian inference for generalized linear models via quasi-posteriors () Generalized linear models (GLMs) are routinely used for modeling
relationships between a response variable and a set of covariates. The simple
form of a GLM comes with easy interpretability, but also leads to concern
Bayesian inference for generalized linear models via quasi-posteriors () Generalized linear models (GLMs) are routinely used for modeling
relationships between a response variable and a set of covariates. The simple
form of a GLM comes with easy interpretability, but also leads to concern
It's Tutorial Tuesday! Join Drs. Rathouz, Cochran, and Yuan as they simplify power and sample size (PSS) calculations for generalized linear models (GLMs) in R. #ENAR2025
More info: www.enar.org/meetings/spr...
More info: www.enar.org/meetings/spr...
January 28, 2025 at 11:57 PM
It's Tutorial Tuesday! Join Drs. Rathouz, Cochran, and Yuan as they simplify power and sample size (PSS) calculations for generalized linear models (GLMs) in R. #ENAR2025
More info: www.enar.org/meetings/spr...
More info: www.enar.org/meetings/spr...
Today's teaching lab was very hands off for me. So, I spent the time building a mock lecture on GLMs.
I'm trying to better understand how they work from the ground up and feel the best way is to pretend I'm teaching others.
#Statistics
#phdlife #phdchat #phdvoice
I'm trying to better understand how they work from the ground up and feel the best way is to pretend I'm teaching others.
#Statistics
#phdlife #phdchat #phdvoice
March 17, 2025 at 6:16 PM
Today's teaching lab was very hands off for me. So, I spent the time building a mock lecture on GLMs.
I'm trying to better understand how they work from the ground up and feel the best way is to pretend I'm teaching others.
#Statistics
#phdlife #phdchat #phdvoice
I'm trying to better understand how they work from the ground up and feel the best way is to pretend I'm teaching others.
#Statistics
#phdlife #phdchat #phdvoice
one quick thing - I saw GUANinE listed under "...benchmarks that do not fine-tune gLMs" and was a bit confused ?
...a big chunk of that paper was about fine-tuning our hgT5 gLMs (it was actually the whole motivation for GUANinE -- tl;dr we saw strong gains in functional & conservation tasks)
...a big chunk of that paper was about fine-tuning our hgT5 gLMs (it was actually the whole motivation for GUANinE -- tl;dr we saw strong gains in functional & conservation tasks)
September 10, 2025 at 2:43 AM
one quick thing - I saw GUANinE listed under "...benchmarks that do not fine-tune gLMs" and was a bit confused ?
...a big chunk of that paper was about fine-tuning our hgT5 gLMs (it was actually the whole motivation for GUANinE -- tl;dr we saw strong gains in functional & conservation tasks)
...a big chunk of that paper was about fine-tuning our hgT5 gLMs (it was actually the whole motivation for GUANinE -- tl;dr we saw strong gains in functional & conservation tasks)
Benchmarking Pre-trained Genomic Language Models for RNA Sequence-Related Predictive Applications [new]
gLMs for RNA: biological info vital; data needs key.
gLMs for RNA: biological info vital; data needs key.
March 11, 2025 at 5:37 AM
Benchmarking Pre-trained Genomic Language Models for RNA Sequence-Related Predictive Applications [new]
gLMs for RNA: biological info vital; data needs key.
gLMs for RNA: biological info vital; data needs key.
Generalized nonlinear models in nnetsauce
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
September 30, 2025 at 6:54 PM
Generalized nonlinear models in nnetsauce
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
#MyYearInMix #MyYearInMix2005
14. "Isabella County, 1992," Great Lakes Myth Society
If there is one song in this #MusicChallenge I want to highlight, it's this accordion-led folk ballad about college life in Mount Pleasant, MI. GLMS is not well know, and that's a tragedy.
youtu.be/WBAdCgqxCjY?...
14. "Isabella County, 1992," Great Lakes Myth Society
If there is one song in this #MusicChallenge I want to highlight, it's this accordion-led folk ballad about college life in Mount Pleasant, MI. GLMS is not well know, and that's a tragedy.
youtu.be/WBAdCgqxCjY?...
Isabella County, 1992
YouTube video by Great Lakes Myth Society - Topic
youtu.be
September 14, 2024 at 12:22 AM
#MyYearInMix #MyYearInMix2005
14. "Isabella County, 1992," Great Lakes Myth Society
If there is one song in this #MusicChallenge I want to highlight, it's this accordion-led folk ballad about college life in Mount Pleasant, MI. GLMS is not well know, and that's a tragedy.
youtu.be/WBAdCgqxCjY?...
14. "Isabella County, 1992," Great Lakes Myth Society
If there is one song in this #MusicChallenge I want to highlight, it's this accordion-led folk ballad about college life in Mount Pleasant, MI. GLMS is not well know, and that's a tragedy.
youtu.be/WBAdCgqxCjY?...
📢 New GLMS lecture on 10 July! From 14:00-15.00, Bert Otten will give a lecture on 'Recording movements'🚶 💃 🏃♀️. And it's a special edition, because Bert Otten will open his photo exhibit📷 Location: Anda Kerkhoven Centre, room 0030, Antonius Deusinglaan 3.
Welcome! 👉 www.rug.nl/umcg/educati...
Welcome! 👉 www.rug.nl/umcg/educati...
Groningen Lectures in Movement Sciences 2024-2025
Four (or more) times a year the department of Human Movement Sciences organizes the ‘Groningen Lectures in Movement Sciences’ (GLMS). In this series,...
www.rug.nl
June 25, 2025 at 9:55 AM
📢 New GLMS lecture on 10 July! From 14:00-15.00, Bert Otten will give a lecture on 'Recording movements'🚶 💃 🏃♀️. And it's a special edition, because Bert Otten will open his photo exhibit📷 Location: Anda Kerkhoven Centre, room 0030, Antonius Deusinglaan 3.
Welcome! 👉 www.rug.nl/umcg/educati...
Welcome! 👉 www.rug.nl/umcg/educati...
Generalized nonlinear models in nnetsauce
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
July 2, 2025 at 8:08 PM
Generalized nonlinear models in nnetsauce
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2020/11/28/explainableml/python/glms
#Techtonique #DataScience #Python #rstats #MachineLearning
gLMs provide promise in learning structure in the genome, but we need to rethink how we either tokenize the genome (and no byte pair encoding isn't the answer either) or come up with a better masking strategy for non-coding genome that is different from other regions (eg coding).
July 16, 2025 at 12:15 PM
gLMs provide promise in learning structure in the genome, but we need to rethink how we either tokenize the genome (and no byte pair encoding isn't the answer either) or come up with a better masking strategy for non-coding genome that is different from other regions (eg coding).
Nonlinear conformalized Generalized Linear Models (GLMs) with R package 'rvfl' (and other models)
https://thierrymoudiki.github.io/blog/2025/03/31/r/glm-zeroinfl
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/03/31/r/glm-zeroinfl
#Techtonique #DataScience #Python #rstats #MachineLearning
June 2, 2025 at 8:18 AM
Nonlinear conformalized Generalized Linear Models (GLMs) with R package 'rvfl' (and other models)
https://thierrymoudiki.github.io/blog/2025/03/31/r/glm-zeroinfl
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/03/31/r/glm-zeroinfl
#Techtonique #DataScience #Python #rstats #MachineLearning
Extending the Theta forecasting method to GLMs and attention
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
June 5, 2025 at 2:37 PM
Extending the Theta forecasting method to GLMs and attention
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/04/08/r/python/glm-thetaf
#Techtonique #DataScience #Python #rstats #MachineLearning