Rishabh (in SF) (@rishabh16

Rishabh (in SF)

9,484 posts

Rishabh (in SF)

@rishabh16_

AI for structural biology @stanford • mech interp for BioML • prev @yale @genentech @cambridge_cl 🧬🛠

🇺🇸🇸🇬

Joined June 2017

Pinned
Rishabh (in SF)
@rishabh16_
Mar 20, 2022
🚨 My Graph Deep Learning extended tutorial has a new home!!! It's finally up on my personal website: rish-16.github.io/posts/gnn-math/ Do RT, share, and tag your GDL buddies if you find it useful 🙌🏻🙌🏻
Rishabh (in SF)
@rishabh16_
Dec 10, 2021
🚨NEW WEEKEND READING🚨 I'm publishing "Graph Neural Networks for Novice Math Fanatics" – a primer on the math behind GNNs using colourful drawings & diagrams rish16.notion.site/Graph-Neural-N… (I hope this becomes the definitive guide to GDL for those hoping to enter the field!!!)
Rishabh (in SF)
@rishabh16_
Mar 2, 2021
Hey 👋🏻 Lately, I've been preparing for ML/DS internship interviews (mainly in Computer Vision) and decided to create a non-exhaustive set of notes to study. Thought I'd share it here for those in the same boat :D notion.so/Machine-Learni… Happy learning!
Rishabh (in SF)
@rishabh16_
Feb 12, 2024
My two contenders: 1) Why LayerNorm is so helpful in Attention and what it’s actually doing under the hood (arxiv.org/abs/2305.02582) 2) Explaining the oversquashing phenomenon in GNNs (arxiv.org/abs/2006.05205) Really cool papers with superrr approachable math/theory 🙌🏻
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Rishabh (in SF)
@rishabh16_
May 29, 2021
Hey 👋🏻 So a lot of you reached out to learn how to train your own models on *ALL* 8 cores of a Colab TPU using @PyTorch XLA Not many good resources out there, so I wrote a super easy 8-step tutorial on doing exactly this: rishtech.substack.com/p/xla-tpu Share if useful :D
8-Core Training via PyTorch XLA on TPUs 🏎
From rishtech.substack.com
Rishabh (in SF)
@rishabh16_
Oct 4, 2023
CS kids will do everything except study for a non-CS exam ...
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Rishabh (in SF)
@rishabh16_
Jan 27, 2022
OpenAI’s embeddings will usher in a new age of vector search engines in latent spaces. Info retrieval’s coming back hotter than ever 🤔 🤔
Rishabh (in SF)
@rishabh16_
Aug 23, 2021
I’m teaching my first ‘Intro to ML’ class at NUS today!!! So excited omg 😍🤩 25 students but fully online. Oh well let’s see how it goes 🤔
Rishabh (in SF)
@rishabh16_
Dec 7, 2021
gm 🚨🚨 New primer on "Math behind Graph Neural Networks and its Variants" dropping soon 👀👀 It's filled with drawings and diagrams too!!! Stay tuned!
Rishabh (in SF)
@rishabh16_
Oct 4, 2025
This is a super cool topic! I did a class project with a friend for a course on Kernels during senior year in college 🔗: github.com/rish-16/ma4270… Lots of fun connections between kernels and self-attention, especially when learning periodic functions The attention patterns
Peyman Milanfar
@docmilanfar
Oct 4, 2025
How Kernel Regression is related to Attention Mechanism - a summary in 10 slides. 0/1
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Rishabh (in SF)
@rishabh16_
Dec 18, 2023
There’s a lot of math involved in current generative models. This is my favourite in-depth blog series about it all by @ludiXIVwinkler: ludwigwinkler.github.io/blog/
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Rishabh (in SF)
@rishabh16_
Jan 24, 2023
Happy Lunar NY 🎉 Just read @PetarV_93's "Everything is Connected". I spent most of 2022 studying Transformers for graphs and this paper intuitively connects most of what I've learned! 🔗: arxiv.org/abs/2301.08210 Here's an executive summary if you haven't caught it yet! 1/9
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Rishabh (in SF)
@rishabh16_
Sep 15, 2024
UPDATE –– I graduated from NUS and have joined @Yale for my masters 🎓 I'll also be working on geometric DL + generative modeling problems in AI4Science with Rex Ying and @KrishnaswamyLab 🧬🤖 Grateful for all the support so far, super excited for what's to come ❤️ #GoBulldogs
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Rishabh (in SF)
@rishabh16_
Feb 20, 2022
🚨🚨 Exciting Update: I've giving a talk on the Expressiveness of Graph Neural Networks at the ✨Workshop on Advances in Deep Learning and Applications✨ this Thursday!! (wadla.in) It's hosted by the Dept of Sci & Tech, Govt. of India 😱 Stay tuned for slides!!!