Xi (Nicole) Zhang
@NZhang211
MD-PhD student @mcgillu & @Mila_Quebec with @Yoshua_Bengio and Mathieu Blanchette | AI + Medicine | Generative models, Flow Matching | Vanier scholar
🚨 New paper alert! [NeurIPS 2024 spotlight] 🚨 Trajectory Flow Matching with Applications to Clinical Time Series Modeling ⏳📈 With: @yuanpu__ , @YukiKawamura_ , Andrew Loza, @Yoshua_Bengio, @dlshung, @AlexanderTong7 💻: github.com/nZhangx/Trajec… 📄: arxiv.org/abs/2410.21154 🧵👇
![NZhang211's tweet image. 🚨 New paper alert! [NeurIPS 2024 spotlight] 🚨
Trajectory Flow Matching with Applications to Clinical Time Series Modeling ⏳📈
With: @yuanpu__ , @YukiKawamura_ , Andrew Loza, @Yoshua_Bengio, @dlshung, @AlexanderTong7
💻: github.com/nZhangx/Trajec…
📄: arxiv.org/abs/2410.21154
🧵👇](https://pbs.twimg.com/media/GbEmZv9aQAAOS_i.jpg)
Congratulations to Thomas Jiralerspong (UdeM), Austin Kraft (McGill) and Nicole Zhang (McGill), three Mila students awarded the 2025 Vanier Scholarship! #vaniercanada View all 2025 recipients vanier.gc.ca/en/scholar_sea…
We’re presenting Meta Flow Matching now in Hall 3 poster #13!! Come by and say hi! #ICLR2025 @NZhang211
🚀Introducing — Meta Flow Matching (MFM) 🚀 Imagine predicting patient-specific treatment responses for unseen cases or building generative models that adapt across different measures. MFM makes this a reality. 📰Paper: arxiv.org/abs/2408.14608 💻Code: github.com/lazaratan/meta…
We've been sharing these projects during the year, but today, they have been accepted at #ICLR2025 (1-3) and #AISTATS2025 (4) 1. The Superposition of Diffusion Models Using the Itô Density Estimator arxiv.org/abs/2412.17762 2. Meta Flow Matching: Integrating Vector Fields on the…
Nicole Zhang (@NZhang211) is presenting her spotlight poster "Trajectory Flow Matching with Applications to Clinical Time Series Modelling" at @NeurIPSConf' Poster Session 5 East, #1002. Here is a short overview of her research.
🧩One less missing piece to cell modelling? Our recent work 𝐌𝐞𝐭𝐚 𝐅𝐥𝐨𝐰 𝐌𝐚𝐭𝐜𝐡𝐢𝐧𝐠 incorporates principles in cancer biology - 𝐭𝐮𝐦𝐨𝐮𝐫 𝐦𝐢𝐜𝐫𝐨𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 to flow matching. And it generalize better to out-of-sample distributions! 🚀
🚀Introducing — Meta Flow Matching (MFM) 🚀 Imagine predicting patient-specific treatment responses for unseen cases or building generative models that adapt across different measures. MFM makes this a reality. 📰Paper: arxiv.org/abs/2408.14608 💻Code: github.com/lazaratan/meta…
We had a great time at our first MD-PhD retreat!
👋I'm Nicole (@NZhang211). I'm an incoming MD-PhD student at McGill University. I develop and optimize Machine Learning models to better understand and predict biological data. On my spare time, I like to bake, paint and do photography.
🔴@mcgillu is red 🔵@CMA_Docs backpacks are blue 🔴The McGill MD-PhD program welcomes you!
Hi #MedTwitter ! It's really starting to kick in - I think we're finally ready for Med1 of our MD/PhD education @mcgillu . Thank you @CMA_Docs for the backpacks!!
Today we announced a $180M Series C financing, which will allow us to expand our #AI discovery platform for 'Programmable' RNA therapeutics and support the advancement of our portfolio into the clinic. More here: bit.ly/2UVS3T2 #deeplearning #genomics #financing #biotech
A little side project I worked on. Can ML methods predict with little data? 👀
Forecasting COVID-19 cases using Machine Learning models medrxiv.org/cgi/content/sh… #medRxiv
Forecasting COVID-19 cases using Machine Learning models medrxiv.org/cgi/content/sh… #medRxiv