Zhidi Lin
@zhidilin.bsky.social
Assistant Professor at EdUHK 🇭🇰🇨🇳 | Machine Learning | Generative Models | Bayesian Inference
🌐 https://zhidi-lin.github.io/
🐦 https://x.com/Zhidi_LIN
🌐 https://zhidi-lin.github.io/
🐦 https://x.com/Zhidi_LIN
Reposted by Zhidi Lin
TMLR has faced a deluge of submissions, necessitating stricter desk rejection policies due to limited reviewer capacity
Co-EiC Nihar Shah reached out to authors of 10 papers slated for desk reject. Could they answer questions about their *own* submission?
medium.com/@TmlrOrg/ask...
Co-EiC Nihar Shah reached out to authors of 10 papers slated for desk reject. Could they answer questions about their *own* submission?
medium.com/@TmlrOrg/ask...
Asking Authors About Their Own Papers
By Nihar B. Shah
medium.com
September 16, 2026 at 8:33 PM
TMLR has faced a deluge of submissions, necessitating stricter desk rejection policies due to limited reviewer capacity
Co-EiC Nihar Shah reached out to authors of 10 papers slated for desk reject. Could they answer questions about their *own* submission?
medium.com/@TmlrOrg/ask...
Co-EiC Nihar Shah reached out to authors of 10 papers slated for desk reject. Could they answer questions about their *own* submission?
medium.com/@TmlrOrg/ask...
Excited to share that I’ll soon be joining the Department of Mathematics and Information Technology at The Education University of Hong Kong (EdUHK) as an Assistant Professor! 🎉
Looking forward to the new journey, new collaborations, and all the opportunities ahead.
Looking forward to the new journey, new collaborations, and all the opportunities ahead.
September 17, 2026 at 4:13 PM
Excited to share that I’ll soon be joining the Department of Mathematics and Information Technology at The Education University of Hong Kong (EdUHK) as an Assistant Professor! 🎉
Looking forward to the new journey, new collaborations, and all the opportunities ahead.
Looking forward to the new journey, new collaborations, and all the opportunities ahead.
First day and the chicken rice @ HKU
July 2, 2025 at 9:41 AM
First day and the chicken rice @ HKU
Reposted by Zhidi Lin
AI that can improve itself: A deep dive into self-improving AI and the Darwin-Gödel Machine.
richardcsuwandi.github.io/blog/2025/dgm/
Excellent blog post by Richard Suwandi reviewing the Darwin Gödel Machine (DGM) and future implications.
richardcsuwandi.github.io/blog/2025/dgm/
Excellent blog post by Richard Suwandi reviewing the Darwin Gödel Machine (DGM) and future implications.
June 4, 2025 at 10:03 AM
AI that can improve itself: A deep dive into self-improving AI and the Darwin-Gödel Machine.
richardcsuwandi.github.io/blog/2025/dgm/
Excellent blog post by Richard Suwandi reviewing the Darwin Gödel Machine (DGM) and future implications.
richardcsuwandi.github.io/blog/2025/dgm/
Excellent blog post by Richard Suwandi reviewing the Darwin Gödel Machine (DGM) and future implications.
Duffing oscillator
en.wikipedia.org/wiki/Duffing...
en.wikipedia.org/wiki/Duffing...
June 6, 2025 at 4:03 PM
Duffing oscillator
en.wikipedia.org/wiki/Duffing...
en.wikipedia.org/wiki/Duffing...
Reposted by Zhidi Lin
Make sure to get your tickets to AABI if you are in Singapore on April 29 (just after #ICLR2025) and interested in probabilistic modeling, inference, and decision-making!
Tickets (free but limited!): lu.ma/5syzr79m
More info: approximateinference.org
#Bayes #MachineLearning #ICLR2025 #AABI2025
Tickets (free but limited!): lu.ma/5syzr79m
More info: approximateinference.org
#Bayes #MachineLearning #ICLR2025 #AABI2025
April 13, 2025 at 7:43 AM
Make sure to get your tickets to AABI if you are in Singapore on April 29 (just after #ICLR2025) and interested in probabilistic modeling, inference, and decision-making!
Tickets (free but limited!): lu.ma/5syzr79m
More info: approximateinference.org
#Bayes #MachineLearning #ICLR2025 #AABI2025
Tickets (free but limited!): lu.ma/5syzr79m
More info: approximateinference.org
#Bayes #MachineLearning #ICLR2025 #AABI2025
Reposted by Zhidi Lin
These sparse Gaussian Processes have been around longer than some grad students, but still fun to code! (and today was my first time coding one...)
April 19, 2025 at 3:18 PM
These sparse Gaussian Processes have been around longer than some grad students, but still fun to code! (and today was my first time coding one...)
Reposted by Zhidi Lin
I already advertised for this document when I posted it on arXiv, and later when it was published.
This week, with the agreement of the publisher, I uploaded the published version on arXiv.
Less typos, more references and additional sections including PAC-Bayes Bernstein.
arxiv.org/abs/2110.11216
This week, with the agreement of the publisher, I uploaded the published version on arXiv.
Less typos, more references and additional sections including PAC-Bayes Bernstein.
arxiv.org/abs/2110.11216
March 5, 2025 at 1:16 AM
I already advertised for this document when I posted it on arXiv, and later when it was published.
This week, with the agreement of the publisher, I uploaded the published version on arXiv.
Less typos, more references and additional sections including PAC-Bayes Bernstein.
arxiv.org/abs/2110.11216
This week, with the agreement of the publisher, I uploaded the published version on arXiv.
Less typos, more references and additional sections including PAC-Bayes Bernstein.
arxiv.org/abs/2110.11216
This paper on sparse variational Gaussian processes is quite intriguing... I always find great enjoyment in reading Titsias's work.
link 📈🤖
New Bounds for Sparse Variational Gaussian Processes (Titsias) Sparse variational Gaussian processes (GPs) construct tractable posterior approximations to GP models. At the core of these methods is the assumption that the true posterior distribution over training function values ${\bf f}$
New Bounds for Sparse Variational Gaussian Processes (Titsias) Sparse variational Gaussian processes (GPs) construct tractable posterior approximations to GP models. At the core of these methods is the assumption that the true posterior distribution over training function values ${\bf f}$
February 26, 2025 at 5:34 PM
This paper on sparse variational Gaussian processes is quite intriguing... I always find great enjoyment in reading Titsias's work.
Reposted by Zhidi Lin
Diffusion Without Tears Discussion
Notion – The all-in-one workspace for your notes, tasks, wikis, and databases.
A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team
baincapitalventures.notion.site
February 14, 2025 at 9:00 PM
Diffusion Without Tears Discussion
Reposted by Zhidi Lin
Excited to share our ICLR 2025 oral "Residual Deep Gaussian Processes on Manifolds"!
With @vabor112.bsky.social & @arkrause.bsky.social, we introduce manifold-to-manifold GPs that can be composed together, generalising deep GPs to manifolds. Applications include wind prediction & Bayes opt! 1/n
With @vabor112.bsky.social & @arkrause.bsky.social, we introduce manifold-to-manifold GPs that can be composed together, generalising deep GPs to manifolds. Applications include wind prediction & Bayes opt! 1/n
February 13, 2025 at 4:45 PM
Excited to share our ICLR 2025 oral "Residual Deep Gaussian Processes on Manifolds"!
With @vabor112.bsky.social & @arkrause.bsky.social, we introduce manifold-to-manifold GPs that can be composed together, generalising deep GPs to manifolds. Applications include wind prediction & Bayes opt! 1/n
With @vabor112.bsky.social & @arkrause.bsky.social, we introduce manifold-to-manifold GPs that can be composed together, generalising deep GPs to manifolds. Applications include wind prediction & Bayes opt! 1/n
Reposted by Zhidi Lin
The deadline for abstract submission of contributed papers and posters for BayesComp2025 has been extended to 28 February. Decisions by 14 March. Submit here! bayescomp2025.sg/abstract-sub...
The deadline for early bird registration has been extended to March 22. Hope to see you in Singapore!
The deadline for early bird registration has been extended to March 22. Hope to see you in Singapore!
Bayes Comp 2025
bayescomp2025.sg
February 13, 2025 at 8:24 PM
The deadline for abstract submission of contributed papers and posters for BayesComp2025 has been extended to 28 February. Decisions by 14 March. Submit here! bayescomp2025.sg/abstract-sub...
The deadline for early bird registration has been extended to March 22. Hope to see you in Singapore!
The deadline for early bird registration has been extended to March 22. Hope to see you in Singapore!
Nothing compares to the moment my newborn smiled at me. Pure, unfiltered joy and love. My heart is so full... 🥹💖
February 15, 2025 at 11:11 AM
Nothing compares to the moment my newborn smiled at me. Pure, unfiltered joy and love. My heart is so full... 🥹💖
Check out our paper if you’re interested: ieeexplore.ieee.org/document/108...
January 30, 2025 at 6:01 AM
Check out our paper if you’re interested: ieeexplore.ieee.org/document/108...
2. The SLIM-KL framework, combining quantized ADMM for privacy and communication efficiency with Distributed Successive Convex Approximation for scalable optimization.
3. Theoretical convergence guarantees and superior performance on diverse datasets, showcasing scalability and efficiency.
3. Theoretical convergence guarantees and superior performance on diverse datasets, showcasing scalability and efficiency.
In this work, we addressed challenges in Gaussian process (GP) regression for multidimensional and large-scale data. Our key contributions:
1. A new GP kernel that reduces hyperparameters while maintaining strong performance, promoting sparsity for efficient optimization.
1. A new GP kernel that reduces hyperparameters while maintaining strong performance, promoting sparsity for efficient optimization.
Thrilled to share that our paper has been accepted by IEEE TNNLS! This is my first journal paper as a mentor and a co-first author. I’m incredibly proud to have collaborated with @richardcsuwandi.bsky.social. Richard’s dedication made this a truly rewarding experience.
January 30, 2025 at 6:00 AM
2. The SLIM-KL framework, combining quantized ADMM for privacy and communication efficiency with Distributed Successive Convex Approximation for scalable optimization.
3. Theoretical convergence guarantees and superior performance on diverse datasets, showcasing scalability and efficiency.
3. Theoretical convergence guarantees and superior performance on diverse datasets, showcasing scalability and efficiency.
In this work, we addressed challenges in Gaussian process (GP) regression for multidimensional and large-scale data. Our key contributions:
1. A new GP kernel that reduces hyperparameters while maintaining strong performance, promoting sparsity for efficient optimization.
1. A new GP kernel that reduces hyperparameters while maintaining strong performance, promoting sparsity for efficient optimization.
Thrilled to share that our paper has been accepted by IEEE TNNLS! This is my first journal paper as a mentor and a co-first author. I’m incredibly proud to have collaborated with @richardcsuwandi.bsky.social. Richard’s dedication made this a truly rewarding experience.
January 30, 2025 at 5:59 AM
In this work, we addressed challenges in Gaussian process (GP) regression for multidimensional and large-scale data. Our key contributions:
1. A new GP kernel that reduces hyperparameters while maintaining strong performance, promoting sparsity for efficient optimization.
1. A new GP kernel that reduces hyperparameters while maintaining strong performance, promoting sparsity for efficient optimization.
Thrilled to share that our paper has been accepted by IEEE TNNLS! This is my first journal paper as a mentor and a co-first author. I’m incredibly proud to have collaborated with @richardcsuwandi.bsky.social. Richard’s dedication made this a truly rewarding experience.
January 30, 2025 at 5:58 AM
Thrilled to share that our paper has been accepted by IEEE TNNLS! This is my first journal paper as a mentor and a co-first author. I’m incredibly proud to have collaborated with @richardcsuwandi.bsky.social. Richard’s dedication made this a truly rewarding experience.
Reposted by Zhidi Lin
One #postdoc position is still available at the National University of Singapore (NUS) to work on sampling, high-dimensional data-assimilation, and diffusion/flow models. Applications are open until the end of January. Details:
alexxthiery.github.io/jobs/2024_di...
alexxthiery.github.io/jobs/2024_di...
December 15, 2024 at 2:46 PM
One #postdoc position is still available at the National University of Singapore (NUS) to work on sampling, high-dimensional data-assimilation, and diffusion/flow models. Applications are open until the end of January. Details:
alexxthiery.github.io/jobs/2024_di...
alexxthiery.github.io/jobs/2024_di...
Langevin Monte Carlo (LMC). Just tried to generate a video to visualize the process 😀
December 14, 2024 at 10:38 AM
Langevin Monte Carlo (LMC). Just tried to generate a video to visualize the process 😀
Reposted by Zhidi Lin
Inventors of flow matching have released a comprehensive guide going over the math & code of flow matching!
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
December 10, 2024 at 8:35 AM
Inventors of flow matching have released a comprehensive guide going over the math & code of flow matching!
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
Also covers variants like non-Euclidean & discrete flow matching.
A PyTorch library is also released with this guide!
This looks like a very good read! 🔥
arxiv: arxiv.org/abs/2412.06264
Reposted by Zhidi Lin
A common question nowadays: Which is better, diffusion or flow matching? 🤔
Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.
Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.
December 2, 2024 at 6:45 PM
A common question nowadays: Which is better, diffusion or flow matching? 🤔
Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.
Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.
Reposted by Zhidi Lin
The 41st Conference on #Uncertainty in #AI will be held in Rio de Janeiro 🇧🇷, July 21-25!
The CfP is out 👉 www.auai.org/uai2025/call...
🚨 Feb 10: Paper submission
🗣️ Apr 3-10: rebuttal period
🎉/💀 May 6: Author notification
#UAI2025 #ML #stats #learning #reasoning #uncertainty
The CfP is out 👉 www.auai.org/uai2025/call...
🚨 Feb 10: Paper submission
🗣️ Apr 3-10: rebuttal period
🎉/💀 May 6: Author notification
#UAI2025 #ML #stats #learning #reasoning #uncertainty
December 3, 2024 at 5:07 PM
The 41st Conference on #Uncertainty in #AI will be held in Rio de Janeiro 🇧🇷, July 21-25!
The CfP is out 👉 www.auai.org/uai2025/call...
🚨 Feb 10: Paper submission
🗣️ Apr 3-10: rebuttal period
🎉/💀 May 6: Author notification
#UAI2025 #ML #stats #learning #reasoning #uncertainty
The CfP is out 👉 www.auai.org/uai2025/call...
🚨 Feb 10: Paper submission
🗣️ Apr 3-10: rebuttal period
🎉/💀 May 6: Author notification
#UAI2025 #ML #stats #learning #reasoning #uncertainty
Reposted by Zhidi Lin
Generating cat videos is nice, but what if you could tackle real scientific problems with the same methods? 🧪🌌
Introducing The Well: 16 datasets (15TB) for Machine Learning, from astrophysics to fluid dynamics and biology.
🐙: github.com/PolymathicAI...
📜: openreview.net/pdf?id=00Sx5...
Introducing The Well: 16 datasets (15TB) for Machine Learning, from astrophysics to fluid dynamics and biology.
🐙: github.com/PolymathicAI...
📜: openreview.net/pdf?id=00Sx5...
December 2, 2024 at 4:08 PM
Generating cat videos is nice, but what if you could tackle real scientific problems with the same methods? 🧪🌌
Introducing The Well: 16 datasets (15TB) for Machine Learning, from astrophysics to fluid dynamics and biology.
🐙: github.com/PolymathicAI...
📜: openreview.net/pdf?id=00Sx5...
Introducing The Well: 16 datasets (15TB) for Machine Learning, from astrophysics to fluid dynamics and biology.
🐙: github.com/PolymathicAI...
📜: openreview.net/pdf?id=00Sx5...