An exhaustive guide to
Explainable AI for Material
Science & Informatics
High-performance Machine
Learning / AI algorithms
have been inadequate in
precisely explaining their
so-called accurate
predictions.
In the majority of cases, there are fundamental issues ( overfitting, high
complexity, generalization errors ) with the models and/or the process that
haunt engineers later, after they’ve invested a significant amount of time and
resources, eventually finding out the discrepancy.
Our team of experts ( Polymer and AI Scientists ) solved this problem
by using a comprehensive closed-loop strategy.
The AI engineers made sure
they open the black-box
models (with explainability
and interpretability), to
quantify and highlight
relationships between the
input formulations and output
properties in the data.
Consequently, Polymer Scientists were responsible for analyzing
and validating given relationships with academic research and
development frameworks of the industry before approving the
model for usage.
Power your materials
research with Polymerize
today
Contact Us:
Address:
Polymerize, 11 IRVING PLACE, #09-01,
Singapore, Singapore 369551
Business mail:
[email protected]
Phone:
+65 3138 5586