Andreas Kirsch
@blackhc.bsky.social
My opinions only here.
👨🔬 RS DeepMind
Past:
👨🔬 R Midjourney 1y 🧑🎓 DPhil AIMS Uni of Oxford 4.5y
🧙♂️ RE DeepMind 1y 📺 SWE Google 3y 🎓 TUM
👤 @nwspk
👨🔬 RS DeepMind
Past:
👨🔬 R Midjourney 1y 🧑🎓 DPhil AIMS Uni of Oxford 4.5y
🧙♂️ RE DeepMind 1y 📺 SWE Google 3y 🎓 TUM
👤 @nwspk
Practical Example:
An active learning experiment on MNIST using a LeNet-5 model with Monte Carlo dropout selecting via BALD scores (expected information gain).
We can visualize how sample informativeness evolves dynamically during training (w/ EMA for visualization):
6/11
An active learning experiment on MNIST using a LeNet-5 model with Monte Carlo dropout selecting via BALD scores (expected information gain).
We can visualize how sample informativeness evolves dynamically during training (w/ EMA for visualization):
6/11
May 17, 2025 at 11:47 AM
Practical Example:
An active learning experiment on MNIST using a LeNet-5 model with Monte Carlo dropout selecting via BALD scores (expected information gain).
We can visualize how sample informativeness evolves dynamically during training (w/ EMA for visualization):
6/11
An active learning experiment on MNIST using a LeNet-5 model with Monte Carlo dropout selecting via BALD scores (expected information gain).
We can visualize how sample informativeness evolves dynamically during training (w/ EMA for visualization):
6/11
Active Learning selects samples iteratively during training (online), while
Data Filtering rejects samples upfront before training starts (offline).
This significantly impacts how we approach data selection, but why should we phrase this as "selection vs. rejection"?
2/11
Data Filtering rejects samples upfront before training starts (offline).
This significantly impacts how we approach data selection, but why should we phrase this as "selection vs. rejection"?
2/11
May 17, 2025 at 11:47 AM
Active Learning selects samples iteratively during training (online), while
Data Filtering rejects samples upfront before training starts (offline).
This significantly impacts how we approach data selection, but why should we phrase this as "selection vs. rejection"?
2/11
Data Filtering rejects samples upfront before training starts (offline).
This significantly impacts how we approach data selection, but why should we phrase this as "selection vs. rejection"?
2/11