Implementing Active Learning Loops to Combat Bias & Improve Model Performance Over Time
Time: 10:00 am
day: Conference Day One
Details:
- Discover how active and continuous learning systems allow models to improve with each new dataset, reducing initial bias
- Examine the impact of bias from datasets favoring only “good” molecules and how this limits model creativity and exploration
- Understand how integrating real-time lab results into training loops supports model refinement and validation
