Update README.md
Browse files
README.md
CHANGED
|
@@ -38,6 +38,13 @@ A geometric deep learning architecture using **Möbius wave interference lenses*
|
|
| 38 |
|
| 39 |
MobiusNet learns frequency-selective sparse coding through three drifting wave functions (L, M, R) combined via learnable XOR/AND logic. The architecture progressively sharpens selectivity through depth, culminating in near-binary winner-take-all gating at the final block.
|
| 40 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 41 |
### Wave Interference Mechanism
|
| 42 |
|
| 43 |
Each Möbius Lens computes:
|
|
|
|
| 38 |
|
| 39 |
MobiusNet learns frequency-selective sparse coding through three drifting wave functions (L, M, R) combined via learnable XOR/AND logic. The architecture progressively sharpens selectivity through depth, culminating in near-binary winner-take-all gating at the final block.
|
| 40 |
|
| 41 |
+
## Primary Concerns
|
| 42 |
+
|
| 43 |
+
The flops are considerably higher than alternative variations. The system DOES WORK, and it does improve the output, but the training time is higher due to the twist in/twist out architectural advantage.
|
| 44 |
+
In the process, you introduce additional uncertainty due to the nature of differentiation. The input must be controlled during distillation and the output must be catered.
|
| 45 |
+
|
| 46 |
+
This experiment was successful, but the optimization isn't there yet to provide a useful solution.
|
| 47 |
+
|
| 48 |
### Wave Interference Mechanism
|
| 49 |
|
| 50 |
Each Möbius Lens computes:
|