diff --git a/experiments/omniglot/model.go b/experiments/omniglot/model.go
index acf65b5..12d5bfd 100644
--- a/experiments/omniglot/model.go
+++ b/experiments/omniglot/model.go
@@ -94,13 +94,13 @@ func normInputLayer(c anyvec.Creator, numOut, numPixels int) anyrnn.Block {
 		Scalers: anydiff.NewVar(c.MakeVector(numPixels + numOut)),
 		Biases:  anydiff.NewVar(c.MakeVector(numPixels + numOut)),
 	}
-	affine.Scalers.Vector.AddScaler(c.MakeNumeric(4))
+	affine.Scalers.Vector.AddScalar(c.MakeNumeric(4))
 
 	modified := affine.Scalers.Vector.Slice(numPixels, numPixels+numOut)
 	modified.Scale(c.MakeNumeric(4))
 
 	modified = affine.Biases.Vector.Slice(0, numPixels)
-	modified.AddScaler(c.MakeNumeric(-4 * 0.92))
+	modified.AddScalar(c.MakeNumeric(-4 * 0.92))
 
 	return &anyrnn.LayerBlock{Layer: affine}
 }
diff --git a/net_test.go b/net_test.go
index f52d838..0a51d2b 100644
--- a/net_test.go
+++ b/net_test.go
@@ -43,7 +43,7 @@ func TestNetTrain(t *testing.T) {
 	target := anydiff.NewVar(targetVec)
 
 	stepSize := c.MakeVector(1)
-	stepSize.AddScaler(c.MakeNumeric(0.1))
+	stepSize.AddScalar(c.MakeNumeric(0.1))
 
 	trained := virtualNet.Train(input, target, anydiff.NewConst(stepSize), 4, 2)
 	actual := trained.Parameters.Outputs()
@@ -136,7 +136,7 @@ func BenchmarkNetwork(b *testing.B) {
 	anyvec.Rand(target.Vector, anyvec.Normal, nil)
 
 	stepSize := anydiff.NewConst(c.MakeVector(1))
-	stepSize.Vector.AddScaler(float32(0.1))
+	stepSize.Vector.AddScalar(float32(0.1))
 
 	b.Run("Forward", func(b *testing.B) {
 		for i := 0; i < b.N; i++ {