Senior Applied Scientist @ AWS AI
#opensource #automl
📊 an online leaderboard (submit!)
📑 carefully curated datasets
📈 strong tree-based, deep learning, and foundation models
🧵
📊 an online leaderboard (submit!)
📑 carefully curated datasets
📈 strong tree-based, deep learning, and foundation models
🧵
Working on tab/ts foundation models (TabPFN/Chronos/etc.)? This is the workshop for you!
📅 Deadline: May 19
🔗 CFP: icml-structured-fm-workshop.github.io/call-for-pap...
Working on tab/ts foundation models (TabPFN/Chronos/etc.)? This is the workshop for you!
📅 Deadline: May 19
🔗 CFP: icml-structured-fm-workshop.github.io/call-for-pap...
✅ Stability & usability improvements
🔥 AutoML Benchmark 2025: AutoGluon is SOTA in tabular ML
🧠 Huge boost to Multimodal with "Bag of Tricks"
📦 Major refactors, bug fixes, and 140+ commits from 20 contributors!
🔗 github.com/autogluon/au...
#OpenSource #AutoML
✅ Stability & usability improvements
🔥 AutoML Benchmark 2025: AutoGluon is SOTA in tabular ML
🧠 Huge boost to Multimodal with "Bag of Tricks"
📦 Major refactors, bug fixes, and 140+ commits from 20 contributors!
🔗 github.com/autogluon/au...
#OpenSource #AutoML
Call for Papers: icml-structured-fm-workshop.github.io
Call for Papers: icml-structured-fm-workshop.github.io
📅 Deadline: March 31
🌐 CfP: 2025.automl.cc
📅 Deadline: March 31
🌐 CfP: 2025.automl.cc
Instead a pre-trained neural network is, the new TabPFN, as we just published in Nature 🎉
Instead a pre-trained neural network is, the new TabPFN, as we just published in Nature 🎉
1. 70% win-rate vs version 1.1.
2. TabPFNMix foundation model, parallel fit
3. AutoGluon-Assistant: Zero-code ML with LLMs.
Also, very cool improvements for TimeSeries related to Chronos!
#AutoML #TabularData
1. 70% win-rate vs version 1.1.
2. TabPFNMix foundation model, parallel fit
3. AutoGluon-Assistant: Zero-code ML with LLMs.
Also, very cool improvements for TimeSeries related to Chronos!
#AutoML #TabularData