Jacobus Dijkman
@jdijkman.bsky.social
Infusing statistical physics with machine learning to describe molecular fluids.
PhD Candidate at UvA with Max Welling, Jan-Willem van de Meent and Bernd Ensing.
PhD Candidate at UvA with Max Welling, Jan-Willem van de Meent and Bernd Ensing.
The key insight: our model learns by observing molecular interactions in simple uniform bulk systems. Once it grasps these patterns, it can predict behavior in complex environments like pores—despite never encountering non-uniform conditions during training.
February 13, 2025 at 9:21 AM
The key insight: our model learns by observing molecular interactions in simple uniform bulk systems. Once it grasps these patterns, it can predict behavior in complex environments like pores—despite never encountering non-uniform conditions during training.
We developed a novel ML approach that rapidly predicts molecular behavior—without running lengthy simulations. 🏎️
February 13, 2025 at 9:21 AM
We developed a novel ML approach that rapidly predicts molecular behavior—without running lengthy simulations. 🏎️
Scientists traditionally rely on computer simulations to understand molecular-level behavior of liquids and gases. However, these simulations can be incredibly time-consuming. ⏳
February 13, 2025 at 9:21 AM
Scientists traditionally rely on computer simulations to understand molecular-level behavior of liquids and gases. However, these simulations can be incredibly time-consuming. ⏳
The key insight: our model learns by observing molecular interactions in simple uniform bulk systems. Once it grasps these patterns, it can predict behavior in complex environments like pores—despite never encountering non-uniform conditions during training.
February 13, 2025 at 9:11 AM
The key insight: our model learns by observing molecular interactions in simple uniform bulk systems. Once it grasps these patterns, it can predict behavior in complex environments like pores—despite never encountering non-uniform conditions during training.
We developed a novel ML approach that rapidly predicts molecular behavior—without running lengthy simulations. 🏎️
February 13, 2025 at 9:11 AM
We developed a novel ML approach that rapidly predicts molecular behavior—without running lengthy simulations. 🏎️
Scientists traditionally rely on computer simulations to understand molecular-level behavior of liquids and gases. However, these simulations can be incredibly time-consuming. ⏳
February 13, 2025 at 9:11 AM
Scientists traditionally rely on computer simulations to understand molecular-level behavior of liquids and gases. However, these simulations can be incredibly time-consuming. ⏳