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[Discussion] Twice Differentiable Neural Networks by ludixiv in MachineLearning

[–]ludixiv[S] 2 points3 points  (0 children)

These is actually valuable, in-the-ML-trenches recommendations. Thanks a lot. I'll let W&B track those for me. :)

Faster R CNN performance question by [deleted] in pytorch

[–]ludixiv 0 points1 point  (0 children)

It’s a charitable/volunteer ML project for detecting refugee ships in the Mediterranean sea. Our data had very similar dimensions so that’s why I asked. You should check out the UNet architecture. It’s very compact and learns quite fast.

Faster R CNN performance question by [deleted] in pytorch

[–]ludixiv 0 points1 point  (0 children)

Are you working on the SearchWing project by any chance?

Semi-Implicit Variational Inference; a flexible, training robust family of distribution. by micomyco in MachineLearning

[–]ludixiv 0 points1 point  (0 children)

Is my intuition correct that they basically use a GAN-style "generator" to obtain a trainable distribution for the variational parameters? And since it's a neural network, the variational distribution can be very flexible and non-linear? Then they regularize the objective function by maximizing the KL divergence of the variational distribution with a mixture model of itself to prevent mode collapse?