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PG conclusions, list formatting

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2021-03-26 10:28:05 +08:00
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physicalloss-discuss.md
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@@ -57,14 +57,14 @@ Bringing these numerical methods back into the picture will be one of the centra
goals of the next sections.
✅ Pro:
- uses physical model
- derivatives can be conveniently compute via backpropagation
- Uses physical model.
- Derivatives can be conveniently compute via backpropagation.
❌ Con:
- quite slow ...
- physical constraints are enforced only as soft constraints
- largely incompatible _classical_ numerical methods
- accuracy of derivatives relies on learned representation
- Quite slow ...
- Physical constraints are enforced only as soft constraints.
- Largely incompatible _classical_ numerical methods.
- Accuracy of derivatives relies on learned representation.
Next, let's look at how we can leverage numerical methods to improve the DL accuracy and efficiency
by making use of differentiable solvers.